Medication adherence and cognitive performance in schizophrenia-spectrum and bipolar disorder: results from the PsyCourse Study.

Existing guidelines recommend psychopharmacological treatment for the management of schizophrenia and bipolar disorder as part of holistic treatment concepts. About half of the patients do not take their medication regularly, although treatment adherence can prevent exacerbations and re-hospitalizations. To date, the relationship between medication adherence and cognitive performance is understudied. Therefore, this study investigated the relationship between medication adherence and cognitive performance by analyzing the data of 862 participants with schizophrenia-spectrum and bipolar disorders (mean [SD] age, 41.9 [12.48] years; 44.8% female) from a multicenter study (PsyCourse Study). Z-scores for three cognitive domains were calculated, global functioning was measured with the Global Assessment of Functioning Scale, and adherence was assessed by a self-rating questionnaire. We evaluated four multiple linear regression models and built three clusters with hierarchical cluster analyses. Higher adherence behavior (p < 0.001) was associated with better global functioning but showed no impact on the cognitive domains learning and memory, executive function, and psychomotor speed. The hierarchical cluster analysis resulted in three clusters with different cognitive performances, but patients in all clusters showed similar adherence behavior. The study identified cognitive subgroups independent of diagnoses, but no differences were found in the adherence behavior of the patients in these new clusters. In summary, medication adherence was associated with global but not cognitive functioning in patients with schizophrenia-spectrum and bipolar disorders. In both diagnostic groups, cognitive function might be influenced by various factors but not medication adherence.

Association of early life stress and cognitive performance in patients with schizophrenia and healthy controls.

As core symptoms of schizophrenia, cognitive deficits contribute substantially to poor outcomes. Early life stress (ELS) can negatively affect cognition in patients with schizophrenia and healthy controls, but the exact nature of the mediating factors is unclear. Therefore, we investigated how ELS, education, and symptom burden are related to cognitive performance. The sample comprised 215 patients with schizophrenia (age, 42.9 ± 12.0 years; 66.0 % male) and 197 healthy controls (age, 38.5 ± 16.4 years; 39.3 % male) from the PsyCourse Study. ELS was assessed with the Childhood Trauma Screener (CTS). We used analyses of covariance and correlation analyses to investigate the association of total ELS load and ELS subtypes with cognitive performance. ELS was reported by 52.1 % of patients and 24.9 % of controls. Independent of ELS, cognitive performance on neuropsychological tests was lower in patients than controls (p < 0.001). ELS load was more closely associated with neurocognitive deficits (cognitive composite score) in controls (r = -0.305, p < 0.001) than in patients (r = -0.163, p = 0.033). Moreover, the higher the ELS load, the more cognitive deficits were found in controls (r = -0.200, p = 0.006), while in patients, this correlation was not significant after adjusting for PANSS. ELS load was more strongly associated with cognitive deficits in healthy controls than in patients. In patients, disease-related positive and negative symptoms may mask the effects of ELS-related cognitive deficits. ELS subtypes were associated with impairments in various cognitive domains. Cognitive deficits appear to be mediated through higher symptom burden and lower educational level.

Machine learning models for predicting severe COVID-19 outcomes in hospitals.

The aim of this observational retrospective study is to improve early risk stratification of hospitalized Covid-19 patients by predicting in-hospital mortality, transfer to intensive care unit (ICU) and mechanical ventilation from electronic health record data of the first 24 h after admission. Our machine learning model predicts in-hospital mortality (AUC = 0.918), transfer to ICU (AUC = 0.821) and the need for mechanical ventilation (AUC = 0.654) from a few laboratory data of the first 24 h after admission. Models based on dichotomous features indicating whether a laboratory value exceeds or falls below a threshold perform nearly as good as models based on numerical features. We devise completely data-driven and interpretable machine-learning models for the prediction of in-hospital mortality, transfer to ICU and mechanical ventilation for hospitalized Covid-19 patients within 24 h after admission. Numerical values of. CRP and blood sugar and dichotomous indicators for increased partial thromboplastin time (PTT) and glutamic oxaloacetic transaminase (GOT) are amongst the best predictors.

Association between mitochondria-related genes and cognitive performance in the PsyCourse Study.

BACKGROUND: Mitochondria generate energy through oxidative phosphorylation (OXPHOS). The function of key OXPHOS proteins can be altered by variation in mitochondria-related genes, which may increase the risk of mental illness. We investigated the association of mitochondria-related genes and their genetic risk burden with cognitive performance. METHODS: We leveraged cross-sectional data from 1320 individuals with a severe psychiatric disorder and 466 neurotypical individuals from the PsyCourse Study. The cognitive tests analyzed were the Trail-Making Test, Verbal Digit Span Test, Digit-Symbol Test, and Multiple Choice Vocabulary Intelligence Test. Association analyses between the cognitive tests, and single-nucleotide polymorphisms (SNPs) mapped to mitochondria-related genes, and their polygenic risk score (PRS) for schizophrenia (SCZ) were performed with PLINK 1.9 and R program. RESULTS: We found a significant association (FDR-adjusted p < 0.05) in the Cytochrome C Oxidase Assembly Factor 8 (COA8) gene locus of the OXPHOS pathway with the Verbal Digit Span (forward) test. Mitochondrial PRS was not significantly associated with any of the cognitive tests. LIMITATIONS: Moderate statistical power due to relatively small sample size. CONCLUSIONS: COA8 encodes a poorly characterized mitochondrial protein involved in apoptosis. Here, this gene was associated with the Verbal Digit Span (forward) test, which evaluates short-term memory. Our results warrant replication and may lead to better understanding of cognitive impairment in mental disorders.

Direct observation of peptide hydrogel self-assembly.

The characterization of self-assembling molecules presents significant experimental challenges, especially when associated with phase separation or precipitation. Transparent window infrared (IR) spectroscopy leverages site-specific probes that absorb in the "transparent window" region of the biomolecular IR spectrum. Carbon-deuterium (C-D) bonds are especially compelling transparent window probes since they are non-perturbative, can be readily introduced site selectively into peptides and proteins, and their stretch frequencies are sensitive to changes in the local molecular environment. Importantly, IR spectroscopy can be applied to a wide range of molecular samples regardless of solubility or physical state, making it an ideal technique for addressing the solubility challenges presented by self-assembling molecules. Here, we present the first continuous observation of transparent window probes following stopped-flow initiation. To demonstrate utility in a self-assembling system, we selected the MAX1 peptide hydrogel, a biocompatible material that has significant promise for use in drug delivery and medical applications. C-D labeled valine was synthetically introduced into five distinct positions of the twenty-residue MAX1 ß-hairpin peptide. Consistent with current structural models, steady-state IR absorption frequencies and linewidths of C-D bonds at all labeled positions indicate that these side chains occupy a hydrophobic region of the hydrogel and that the motion of side chains located in the middle of the hairpin is more restricted than those located on the hairpin ends. Following a rapid change in ionic strength to initiate self-assembly, the peptide absorption spectra were monitored as function of time, allowing determination of site-specific time constants. We find that within the experimental resolution, MAX1 self-assembly occurs as a cooperative process. These studies suggest that stopped-flow transparent window FTIR can be extended to other time-resolved applications, such as protein folding and enzyme kinetics.

A novel longitudinal clustering approach to psychopathology across diagnostic entities in the hospital-based PsyCourse study.

Biological research and clinical management in psychiatry face two major impediments: the high degree of overlap in psychopathology between diagnoses and the inherent heterogeneity with regard to severity. Here, we aim to stratify cases into homogeneous transdiagnostic subgroups using psychometric information with the ultimate aim of identifying individuals with higher risk for severe illness. 397 participants of the PsyCourse study with schizophrenia- or bipolar-spectrum diagnoses were prospectively phenotyped over 18 months. Factor analysis of mixed data of different rating scales and subsequent longitudinal clustering were used to cluster disease trajectories. Five clusters of longitudinal trajectories were identified in the psychopathologic dimensions. Clusters differed significantly with regard to Global Assessment of Functioning, disease course, and-in some cases-diagnosis while there were no significant differences regarding sex, age at baseline or onset, duration of illness, or polygenic burden for schizophrenia. Longitudinal clustering may aid in identifying transdiagnostic homogeneous subgroups of individuals with severe psychiatric disease.

Polygenic risk scores across the extended psychosis spectrum.

As early detection of symptoms in the subclinical to clinical psychosis spectrum may improve health outcomes, knowing the probabilistic susceptibility of developing a disorder could guide mitigation measures and clinical intervention. In this context, polygenic risk scores (PRSs) quantifying the additive effects of multiple common genetic variants hold the potential to predict complex diseases and index severity gradients. PRSs for schizophrenia (SZ) and bipolar disorder (BD) were computed using Bayesian regression and continuous shrinkage priors based on the latest SZ and BD genome-wide association studies (Psychiatric Genomics Consortium, third release). Eight well-phenotyped groups (n = 1580; 56% males) were assessed: control (n = 305), lower (n = 117) and higher (n = 113) schizotypy (both groups of healthy individuals), at-risk for psychosis (n = 120), BD type-I (n = 359), BD type-II (n = 96), schizoaffective disorder (n = 86), and SZ groups (n = 384). PRS differences were investigated for binary traits and the quantitative Positive and Negative Syndrome Scale. Both BD-PRS and SZ-PRS significantly differentiated controls from at-risk and clinical groups (Nagelkerke's pseudo-R2: 1.3-7.7%), except for BD type-II for SZ-PRS. Out of 28 pairwise comparisons for SZ-PRS and BD-PRS, 9 and 12, respectively, reached the Bonferroni-corrected significance. BD-PRS differed between control and at-risk groups, but not between at-risk and BD type-I groups. There was no difference between controls and schizotypy. SZ-PRSs, but not BD-PRSs, were positively associated with transdiagnostic symptomology. Overall, PRSs support the continuum model across the psychosis spectrum at the genomic level with possible irregularities for schizotypy. The at-risk state demands heightened clinical attention and research addressing symptom course specifiers. Continued efforts are needed to refine the diagnostic and prognostic accuracy of PRSs in mental healthcare.

Interplay between the genetics of personality traits, severe psychiatric disorders and COVID-19 host genetics in the susceptibility to SARS-CoV-2 infection.

BACKGROUND: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, with its impact on our way of life, is affecting our experiences and mental health. Notably, individuals with mental disorders have been reported to have a higher risk of contracting SARS-CoV-2. Personality traits could represent an important determinant of preventative health behaviour and, therefore, the risk of contracting the virus. AIMS: We examined overlapping genetic underpinnings between major psychiatric disorders, personality traits and susceptibility to SARS-CoV-2 infection. METHOD: Linkage disequilibrium score regression was used to explore the genetic correlations of coronavirus disease 2019 (COVID-19) susceptibility with psychiatric disorders and personality traits based on data from the largest available respective genome-wide association studies (GWAS). In two cohorts (the PsyCourse (n = 1346) and the HeiDE (n = 3266) study), polygenic risk scores were used to analyse if a genetic association between, psychiatric disorders, personality traits and COVID-19 susceptibility exists in individual-level data. RESULTS: We observed no significant genetic correlations of COVID-19 susceptibility with psychiatric disorders. For personality traits, there was a significant genetic correlation for COVID-19 susceptibility with extraversion (P = 1.47 × 10-5; genetic correlation 0.284). Yet, this was not reflected in individual-level data from the PsyCourse and HeiDE studies. CONCLUSIONS: We identified no significant correlation between genetic risk factors for severe psychiatric disorders and genetic risk for COVID-19 susceptibility. Among the personality traits, extraversion showed evidence for a positive genetic association with COVID-19 susceptibility, in one but not in another setting. Overall, these findings highlight a complex contribution of genetic and non-genetic components in the interaction between COVID-19 susceptibility and personality traits or mental disorders.

A genome-wide association study of the longitudinal course of executive functions.

Executive functions are metacognitive capabilities that control and coordinate mental processes. In the transdiagnostic PsyCourse Study, comprising patients of the affective-to-psychotic spectrum and controls, we investigated the genetic basis of the time course of two core executive subfunctions: set-shifting (Trail Making Test, part B (TMT-B)) and updating (Verbal Digit Span backwards) in 1338 genotyped individuals. Time course was assessed with four measurement points, each 6 months apart. Compared to the initial assessment, executive performance improved across diagnostic groups. We performed a genome-wide association study to identify single nucleotide polymorphisms (SNPs) associated with performance change over time by testing for SNP-by-time interactions using linear mixed models. We identified nine genome-wide significant SNPs for TMT-B in strong linkage disequilibrium with each other on chromosome 5. These were associated with decreased performance on the continuous TMT-B score across time. Variant rs150547358 had the lowest P value = 7.2 × 10-10 with effect estimate beta = 1.16 (95% c.i.: 1.11, 1.22). Implementing data of the FOR2107 consortium (1795 individuals), we replicated these findings for the SNP rs150547358 (P value = 0.015), analyzing the difference of the two available measurement points two years apart. In the replication study, rs150547358 exhibited a similar effect estimate beta = 0.85 (95% c.i.: 0.74, 0.97). Our study demonstrates that longitudinally measured phenotypes have the potential to unmask novel associations, adding time as a dimension to the effects of genomics.

Medication Adherence in a Cross-Diagnostic Sample of Patients From the Affective-to-Psychotic Spectrum: Results From the PsyCourse Study.

INTRODUCTION: 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. METHODS: 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. RESULTS: 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). CONCLUSION: 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.

The role of environmental stress and DNA methylation in the longitudinal course of bipolar disorder.

BACKGROUND: Stressful life events influence the course of affective disorders, however, the mechanisms by which they bring about phenotypic change are not entirely known. METHODS: We explored the role of DNA methylation in response to recent stressful life events in a cohort of bipolar patients from the longitudinal PsyCourse study (n = 96). Peripheral blood DNA methylomes were profiled at two time points for over 850,000 methylation sites. The association between impact ratings of stressful life events and DNA methylation was assessed, first by interrogating methylation sites in the vicinity of candidate genes previously implicated in the stress response and, second, by conducting an exploratory epigenome-wide association analysis. Third, the association between epigenetic aging and change in stress and symptom measures over time was investigated. RESULTS: Investigation of methylation signatures over time revealed just over half of the CpG sites tested had an absolute difference in methylation of at least 1% over a 1-year period. Although not a single CpG site withstood correction for multiple testing, methylation at one site (cg15212455) was suggestively associated with stressful life events (p < 1.0 × 10-5). Epigenetic aging over a 1-year period was not associated with changes in stress or symptom measures. CONCLUSIONS: To the best of our knowledge, our study is the first to investigate epigenome-wide methylation across time in bipolar patients and in relation to recent, non-traumatic stressful life events. Limited and inconclusive evidence warrants future longitudinal investigations in larger samples of well-characterized bipolar patients to give a complete picture regarding the role of DNA methylation in the course of bipolar disorder.

Unsupervised and Generic Short-Term Anticipation of Human Body Motions.

Various neural network based methods are capable of anticipating human body motions from data for a short period of time. What these methods lack are the interpretability and explainability of the network and its results. We propose to use Dynamic Mode Decomposition with delays to represent and anticipate human body motions. Exploring the influence of the number of delays on the reconstruction and prediction of various motion classes, we show that the anticipation errors in our results are comparable to or even better for very short anticipation times ( < 0 . 4 sec) than a recurrent neural network based method. We perceive our method as a first step towards the interpretability of the results by representing human body motions as linear combinations of previous states and delays. In addition, compared to the neural network based methods large training times are not needed. Actually, our methods do not even regress to any other motions than the one to be anticipated and hence it is of a generic nature.

An Investigation of Psychosis Subgroups With Prognostic Validation and Exploration of Genetic Underpinnings: The PsyCourse Study.

Importance: 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. Objective: 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. Design, Setting, and Participants: 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. Main Outcomes and Measures: 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. Results: 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. Conclusions and Relevance: 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.

The genetic relationship between educational attainment and cognitive performance in major psychiatric disorders.

Cognitive deficits are a core feature of psychiatric disorders like schizophrenia and bipolar disorder. Evidence supports a genome-wide polygenic score (GPS) for educational attainment (GPSEDU) can be used to explain variability in cognitive performance. We aimed to identify different cognitive domains associated with GPSEDU in a transdiagnostic clinical cohort of chronic psychiatric patients with known cognitive deficits. Bipolar and schizophrenia patients from the PsyCourse cohort (N = 730; 43% female) were used. Likewise, we tested whether GPSs for schizophrenia (GPSSZ) and bipolar disorder (GPSBD) were associated with cognitive outcomes. GPSEDU explained 1.5% of variance in the backward verbal digit span, 1.9% in the number of correctly recalled words of the Verbal Learning and Memory Test, and 1.1% in crystallized intelligence. These effects were robust to the influences of treatment and diagnosis. No significant associations between GPSSZ or GPSBD with cognitive outcomes were found. Furthermore, these risk scores did not confound the effect of GPSEDU on cognitive outcomes. GPSEDU explains a small fraction of cognitive performance in adults with psychiatric disorders, specifically for domains related to linguistic learning and working memory. Investigating such a proxy-phenotype longitudinally, could give intriguing insight into the disease course, highlighting at what time genes play a more influential role on cognitive performance. Better understanding the origin of these deficits might help identify those patients at risk for lower levels of functioning and poor social outcomes. Polygenic estimates may in the future be part of predictive models for more personalized interventions.

Structure and Dynamics of Stacking Interactions in an Antibody Binding Site.

For years, antibodies (Abs) have been used as a paradigm for understanding how protein structure contributes to molecular recognition. However, with the ability to evolve Abs that recognize specific chromophores, they also have great potential as models for how protein dynamics contribute to molecular recognition. We previously raised murine Abs to different chromophores and, with the use of three-pulse photon echo peak shift spectroscopy, demonstrated that the immune system is capable of producing Abs with widely varying flexibility. We now report the characterization of the complexes formed between two Abs, 5D11 and 10A6, and the chromophoric ligand that they were evolved to recognize, 8-methoxypyrene-1,3,6-trisulfonic acid (MPTS). The sequences of the Ab genes indicate that they evolved from a common precursor. We also used a variety of spectroscopic methods to probe the photophysics and dynamics of the Ab-MPTS complexes and found that they are similar to each other but distinct from previously characterized anti-MPTS Abs. Structural studies revealed that this difference likely results from a unique mode of binding in which MPTS is sandwiched between the side chain of PheH98, which interacts with the chromophore via T-stacking, and the side chain of TrpL91, which interacts with the chromophore via parallel stacking. The T-stacking interaction appears to mediate relaxation on the picosecond time scale, while the parallel stacking appears to mediate relaxation on an ultrafast, femtosecond time scale, which dominates the response. The anti-MPTS Abs thus not only demonstrate the simultaneous use of the two limiting modes of stacking for molecular recognition, but also provide a unique opportunity to characterize how dynamics might contribute to molecular recognition. Both types of stacking are common in proteins and protein complexes where they may similarly contribute to dynamics and molecular recognition.

The influence of religious activity and polygenic schizophrenia risk on religious delusions in schizophrenia.

BACKGROUND: Religious delusions are a common symptom in patients experiencing psychosis, with varying prevalence rates of religious delusions across cultures and societies. To enhance our knowledge of this distinct psychotic feature, we investigated the mutually-adjusted association of genetic and environmental factors with occurrence of religious delusions. METHODS: We studied 262 adult German patients with schizophrenia or schizoaffective disorder. Association with lifetime occurrence of religious delusions was tested by multiple logistic regression for the following putative predictors: self-reported degree of religious activity, DSM-IV diagnosis, sex, age, education level, marital status, presence of acute delusion at the time of interview and an individual polygenic schizophrenia-risk score (SZ-PRS, available in 239 subjects). RESULTS: Of the 262 patients, 101 (39%) had experienced religious delusions. The risk of experiencing religious delusions was significantly increased in patients with strong religious activity compared to patients without religious affiliation (OR = 3.6, p = 0.010). Low or moderate religious activity had no significant effect. The same analysis including the SZ-PRS confirmed the effect of high religious activity on occurrence of religious delusions (OR = 4.1, p = 0.008). Additionally, the risk of experiencing religious delusions increased with higher SZ-PRS (OR 1.4, p = 0.020, using pT = 0.05 for SZ-PRS calculation). None of the other variables were significantly associated with lifetime occurrence of religious delusions. CONCLUSIONS: Our results suggest that strong religious activity and high SZ-PRS are independent risk factors for the occurrence of religious delusions in schizophrenia and schizoaffective disorder.

A longitudinal approach to biological psychiatric research: The PsyCourse study.

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.

Five-year effectiveness of low-dose-rate brachytherapy: comparisons with nomogram predictions in patients with non-metastatic prostate cancer presenting significant control of intra- and periprostatic disease.

PURPOSE: To assess the effectiveness of low-dose-rate (LDR) brachytherapy in patients with localized prostate cancer and to compare the outcome with predictions from Kattan and Partin nomograms at 60 months after seed implantation. MATERIAL AND METHODS: One thousand, one hundred and eighty-seven patients with localized prostate cancer at low-, intermediate-, or high-risk of progression received LDR brachytherapy using iodine-125 seeds with curative intent, applied as monotherapy or in combination with external beam radiation therapy (EBRT), and/or androgen deprivation therapy (ADT). At 60 months after seed implantation, data of 1,064 patients (1,058 alive + 6 who died of prostate cancer) were analyzed for biochemical progression-free survival (bPFS) based on prostate-specific antigen (PSA) levels using the Phoenix definition. Five-year bPFS probabilities were determined for various risk group classifications (d'Amico, Mt. Sinai, MSKCC/Seattle, NCCN). Outcomes were also compared to patient-individualized nomogram predictions of 5-year bPFS (Kattan 2002) and probability of organ-confined disease (Kattan 2002, Partin 2007). RESULTS: Overall, 93.3% (993/1,064) of the patients were free of biochemical progression within 5 years, while the average 5-year bPFS probability according to the Kattan nomogram was significantly lower (85%, p < 0.001). Outcomes were significantly better than Kattan nomogram predictions in the subgroup of patients with monotherapy as well as in patients additionally treated with EBRT. Comparison of the overall outcome with nomogram predictions for organ-confined disease (Kattan nomogram: 50%; Partin nomogram: 65%) revealed a significant probability of LDR brachytherapy to destroy periprostatic tumor spread (p < 0.001) in all risk group constellations, even in high-risk patients. CONCLUSIONS: The results indicate high effectiveness of LDR brachytherapy in all risk groups, significantly better than predicted with the Kattan nomogram in most subgroups. The significant superiority of LDR brachytherapy compared to nomogram predictions of organ-confined disease suggests that LDR brachytherapy effectively controls both intra- and periprostatic disease.

A Simple 3-Parameter Model for Cancer Incidences.

We propose a simple 3-parameter model that provides very good fits for incidence curves of 18 common solid cancers even when variations due to different locations, races, or periods are taken into account. From a data perspective, we use model selection (Akaike information criterion) to show that this model, which is based on the Weibull distribution, outperforms other simple models like the Gamma distribution. From a modeling perspective, the Weibull distribution can be justified as modeling the accumulation of driver events, which establishes a link to stem cell division based cancer development models and a connection to a recursion formula for intrinsic cancer risk published by Wu et al. For the recursion formula a closed form solution is given, which will help to simplify future analyses. Additionally, we perform a sensitivity analysis for the parameters, showing that two of the three parameters can vary over several orders of magnitude. However, the shape parameter of the Weibull distribution, which corresponds to the number of driver mutations required for cancer onset, can be robustly estimated from epidemiological data.