Identifying genetic differences between bipolar disorder and major depression through multiple GWAS.

Background: Accurate diagnosis of bipolar disorder (BD) is difficult in clinical practice, with an average delay between symptom onset and diagnosis of about 7 years. A key reason is that the first manic episode is often preceded by a depressive one, making it difficult to distinguish BD from unipolar major depressive disorder (MDD). Aims: Here, we use genome-wide association analyses (GWAS) to identify differential genetic factors and to develop predictors based on polygenic risk scores that may aid early differential diagnosis. Methods: Based on individual genotypes from case-control cohorts of BD and MDD shared through the Psychiatric Genomics Consortium, we compile case-case-control cohorts, applying a careful merging and quality control procedure. In a resulting cohort of 51,149 individuals (15,532 BD cases, 12,920 MDD cases and 22,697 controls), we perform a variety of GWAS and polygenic risk scores (PRS) analyses. Results: While our GWAS is not well-powered to identify genome-wide significant loci, we find significant SNP-heritability and demonstrate the ability of the resulting PRS to distinguish BD from MDD, including BD cases with depressive onset. We replicate our PRS findings, but not signals of individual loci in an independent Danish cohort (iPSYCH 2015 case-cohort study, N=25,966). We observe strong genetic correlation between our case-case GWAS and that of case-control BD. Conclusions: We find that MDD and BD, including BD with a depressive onset, are genetically distinct. Further, our findings support the hypothesis that Controls - MDD - BD primarily lie on a continuum of genetic risk. Future studies with larger and richer samples will likely yield a better understanding of these findings and enable the development of better genetic predictors distinguishing BD and, importantly, BD with depressive onset from MDD.

Digitalising mental health care: Practical recommendations from the European Psychiatric Association.

The digitalisation of mental health care is expected to improve the accessibility and quality of specialised treatment services and introduce innovative methods to study, assess, and monitor mental health disorders. In this narrative review and practical recommendation of the European Psychiatric Association (EPA), we aim to help healthcare providers and policymakers to navigate this rapidly evolving field. We provide an overview of the current scientific and implementation status across two major domains of digitalisation: i) digital mental health interventions and ii) digital phenotyping, discuss the potential of each domain to improve the accessibility and outcomes of mental health services, and highlight current challenges faced by researchers, clinicians, and service users. Furthermore, we make several recommendations meant to foster the widespread adoption of evidence-based digital solutions for mental health care in the member states of the EPA. To realise the vision of a digitalised, patient-centred, and data-driven mental health ecosystem, a number of implementation challenges must be considered and addressed, spanning from human, technical, ethical-legal, and economic barriers. The list of priority areas and action points our expert panel has identified could serve as a playbook for this process.

Biofilm formation initiating rotifer-specific biopolymer and its predicted components.

The rotifer-specific biopolymer, namely Rotimer, is a recently discovered group of the biomolecule family. Rotimer has an active role in the biofilm formation initiated by rotifers (e.g., Euchlanis dilatata or Adineta vaga) or in the female-male sexual interaction of monogononts. To understand the Ca2+- and polarity-dependent formation of this multifunctional viscoelastic material, it is essential to explore its molecular composition. The investigation of the rotifer-enhanced biofilm and Rotimer-inductor conglomerate (RIC) formation yielded several protein candidates to predict the Rotimer-specific main components. The exudate of E. dilatata males was primarily applied from different biopolimer-containing samples (biofilm or RIC). The advantage of males over females lies in their degenerated digestive system and simple anatomy. Thus, their exudate is less contaminated with food and endosymbiont elements. The sequenced and annotated genome and transcriptome of this species opened the way for identifying Rotimer proteins by mass spectrometry. The predicted rotifer-biopolymer forming components are SCO-spondins and 14-3-3 protein. The characteristics of Rotimer are similar to Reissner's fiber, which is found in the central nervous system of vertebrates and is mainly formed from SCO-spondins. This molecular information serves as a starting point for its interdisciplinary investigation and application in biotechnology, biomedicine, or neurodegeneration-related drug development.

Common genetic variants contribute to heritability of age at onset of schizophrenia.

Schizophrenia (SCZ) is a complex disorder that typically arises in late adolescence or early adulthood. Age at onset (AAO) of SCZ is associated with long-term outcomes of the disease. We explored the genetic architecture of AAO with a genome-wide association study (GWAS), heritability, polygenic risk score (PRS), and copy number variant (CNV) analyses in 4 740 subjects of European ancestry. Although no genome-wide significant locus was identified, SNP-based heritability of AAO was estimated to be between 17 and 21%, indicating a moderate contribution of common variants. We also performed cross-trait PRS analyses with a set of mental disorders and identified a negative association between AAO and common variants for SCZ, childhood maltreatment and attention-deficit/hyperactivity disorder. We also investigated the role of copy number variants (CNVs) in AAO and found an association with the length and number of deletions (P-value = 0.03), whereas the presence of CNVs previously reported in SCZ was not associated with earlier onset. To our knowledge, this is the largest GWAS of AAO of SCZ to date in individuals from European ancestry, and the first study to determine the involvement of common variants in the heritability of AAO. Finally, we evidenced the role played by higher SCZ load in determining AAO but discarded the role of pathogenic CNVs. Altogether, these results shed light on the genetic architecture of AAO, which needs to be confirmed with larger studies.

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.

Genetic contributions to transdiagnostic symptom dimensions in patients with major depressive disorder, bipolar disorder, and schizophrenia spectrum disorders.

Major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia spectrum disorders (SZ) exhibit considerable phenotypic and genetic overlap. However, the contribution of genetic factors to their shared psychopathological symptom dimensions remains unclear. The present exploratory study investigated genetic contributions to the symptom dimensions "Depression", "Negative syndrome", "Positive formal thought disorder", "Paranoid-hallucinatory syndrome", and "Increased appetite" in a transdiagnostic subset of the German FOR2107 cohort (n = 1042 patients with MDD, BD, or SZ). As replication cohort, a subset of the German/Austrian PsyCourse study (n = 816 patients with MDD, BD, or SZ) was employed. First, the relationship between symptom dimensions and common variants associated with MDD, BD, and SZ was investigated via polygenic risk score (PRS) association analyses, with disorder-specific PRS as predictors and symptom dimensions as outcomes. In the FOR2107 study sample, PRS for BD and SZ were positively associated with "Positive formal thought disorder", the PRS for SZ was positively associated with "Paranoid-hallucinatory syndrome", and the PRS for BD was negatively associated with "Depression". The effects of PRS for SZ were replicated in PsyCourse. No significant associations were observed for the MDD PRS. Second, genome-wide association studies (GWAS) were performed for the five symptom dimensions. No genome-wide significant associations and no replicable suggestive associations (p < 1e-6 in the GWAS) were identified. In summary, our results suggest that, similar to diagnostic categories, transdiagnostic psychiatric symptom dimensions are attributable to polygenic contributions with small effect sizes. Further studies in larger thoroughly phenotyped psychiatric cohorts are required to elucidate the genetic factors that shape psychopathological symptom dimensions.

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.

Seasonality and Delirium Tremens in Hospitalized Patients with Alcohol Dependence Syndrome.

INTRODUCTION: Due to the high rate of mortality, recognizing the contributing factors of alcohol-related delirium tremens (DT), which is the most severe form of alcohol withdrawal state (AWS) is pivotal in clinical settings. Previous studies suggested relationship between seasonality and other types of delirium; however, to our knowledge, this is the first empirical study which examined the role of seasonality in DT in alcohol dependence syndrome (ADS). METHODS: A retrospective study was undertaken between 2008 and 2015; medical records of 1,591 patients were included, which yielded 2,900 hospital appearances. Three groups were formed based on the ICD-10 diagnoses: ADS, AWS, and DT. The characteristics of the groups were analysed with one-way ANOVA and χ2 tests. Multinomial logistic regression was used to explore the potential predictors of DT, including seasonality. RESULTS: The highest incidence of DT was in spring (36.8%; χ2 (3) = 27.666; p < 0.001), especially in March (13.9%; χ2 (11) = 33.168; p < 0.001). Spring, higher mean age, higher presence of comorbid somatic disorders, and lower occurrence of comorbid psychiatric disorders were significant predictive variables for DT with the control of socio-demographic and clinical variables. CONCLUSIONS: The present study revealed that spring, especially March is a critical period in temperate climate zone regarding DT. This can be interpreted as a late winter effect since the temperature is lower in this month compared to other spring months. Furthermore, higher age and the occurrence of comorbid somatic disorders can be considered as risk factors in case of DT. These results support the need of further clinical studies to better understand the impact of seasonality on DT.

Lipid Alteration Signature in the Blood Plasma of Individuals With Schizophrenia, Depression, and Bipolar Disorder.

Importance: No clinically applicable diagnostic test exists for severe mental disorders. Lipids harbor potential as disease markers. Objective: To define a reproducible profile of lipid alterations in the blood plasma of patients with schizophrenia (SCZ) independent of demographic and environmental variables and to investigate its specificity in association with other psychiatric disorders, ie, major depressive disorder (MDD) and bipolar disorder (BPD). Design, Setting, and Participants: This was a multicohort case-control diagnostic analysis involving plasma samples from psychiatric patients and control individuals collected between July 17, 2009, and May 18, 2018. Study participants were recruited as consecutive and volunteer samples at multiple inpatient and outpatient mental health hospitals in Western Europe (Germany and Austria [DE-AT]), China (CN), and Russia (RU). Individuals with DSM-IV or International Statistical Classification of Diseases and Related Health Problems, Tenth Revision diagnoses of SCZ, MDD, BPD, or a first psychotic episode, as well as age- and sex-matched healthy controls without a mental health-related diagnosis were included in the study. Samples and data were analyzed from January 2018 to September 2020. Main Outcomes and Measures: Plasma lipidome composition was assessed using liquid chromatography coupled with untargeted mass spectrometry. Results: Blood lipid levels were assessed in 980 individuals (mean [SD] age, 36 [13] years; 510 male individuals [52%]) diagnosed with SCZ, BPD, MDD, or those with a first psychotic episode and in 572 controls (mean [SD] age, 34 [13] years; 323 male individuals [56%]). A total of 77 lipids were found to be significantly altered between those with SCZ (n = 436) and controls (n = 478) in all 3 sample cohorts. Alterations were consistent between cohorts (CN and RU: [Pearson correlation] r = 0.75; DE-AT and CN: r = 0.78; DE-AT and RU: r = 0.82; P < 10-38). A lipid-based predictive model separated patients with SCZ from controls with high diagnostic ability (area under the receiver operating characteristic curve = 0.86-0.95). Lipidome alterations in BPD and MDD, assessed in 184 and 256 individuals, respectively, were found to be similar to those of SCZ (BPD: r = 0.89; MDD: r = 0.92; P < 10-79). Assessment of detected alterations in individuals with a first psychotic episode, as well as patients with SCZ not receiving medication, demonstrated only limited association with medication restricted to particular lipids. Conclusions and Relevance: In this study, SCZ was accompanied by a reproducible profile of plasma lipidome alterations, not associated with symptom severity, medication, and demographic and environmental variables, and largely shared with BPD and MDD. This lipid alteration signature may represent a trait marker of severe psychiatric disorders, indicating its potential to be transformed into a clinically applicable testing procedure.

Mapping Research Domain Criteria using a transdiagnostic mini-RDoC assessment in mental disorders: a confirmatory factor analysis.

This study aimed to build on the relationship of well-established self-report and behavioral assessments to the latent constructs positive (PVS) and negative valence systems (NVS), cognitive systems (CS), and social processes (SP) of the Research Domain Criteria (RDoC) framework in a large transnosological population which cuts across DSM/ICD-10 disorder criteria categories. One thousand four hundred and thirty one participants (42.1% suffering from anxiety/fear-related, 18.2% from depressive, 7.9% from schizophrenia spectrum, 7.5% from bipolar, 3.4% from autism spectrum, 2.2% from other disorders, 18.4% healthy controls, and 0.2% with no diagnosis specified) recruited in studies within the German research network for mental disorders for the Phenotypic, Diagnostic and Clinical Domain Assessment Network Germany (PD-CAN) were examined with a Mini-RDoC-Assessment including behavioral and self-report measures. The respective data was analyzed with confirmatory factor analysis (CFA) to delineate the underlying latent RDoC-structure. A revised four-factor model reflecting the core domains positive and negative valence systems as well as cognitive systems and social processes showed a good fit across this sample and showed significantly better fit compared to a one factor solution. The connections between the domains PVS, NVS and SP could be substantiated, indicating a universal latent structure spanning across known nosological entities. This study is the first to give an impression on the latent structure and intercorrelations between four core Research Domain Criteria in a transnosological sample. We emphasize the possibility of using already existing and well validated self-report and behavioral measurements to capture aspects of the latent structure informed by the RDoC matrix.

The Role of Silence in Verbal Fluency Tasks - A New Approach for the Detection of Mild Cognitive Impairment.

OBJECTIVE: Most recordings of verbal fluency tasks include substantial amounts of task-irrelevant content that could provide clinically valuable information for the detection of mild cognitive impairment (MCI). We developed a method for the analysis of verbal fluency, focusing not on the task-relevant words but on the silent segments, the hesitations, and the irrelevant utterances found in the voice recordings. METHODS: Phonemic ('k', 't', 'a') and semantic (animals, food items, actions) verbal fluency data were collected from healthy control (HC; n = 25; Mage = 67.32) and MCI (n = 25; Mage = 71.72) participants. After manual annotation of the voice samples, 10 temporal parameters were computed based on the silent and the task-irrelevant segments. Traditional fluency measures, based on word count (correct words, errors, repetitions) were also employed in order to compare the outcome of the two methods. RESULTS: Two silence-based parameters (the number of silent pauses and the average length of silent pauses) and the average word transition time differed significantly between the two groups in the case of all three semantic fluency tasks. Subsequent receiver operating characteristic (ROC) analysis showed that these three temporal parameters had classification abilities similar to the traditional measure of counting correct words. CONCLUSION: In our approach for verbal fluency analysis, silence-related parameters displayed classification ability similar to the most widely used traditional fluency measure. Based on these results, an automated tool using voiced-unvoiced segmentation may be developed enabling swift and cost-effective verbal fluency-based MCI screening.

[The role of socialisation in psychosexual development].

INTRODUCTION: In the recent research and interpretation of the genetical-biological and environmental-social factors shaping psychosexual development, in addition to scientific arguments, more and more ideological and political aspect have received unfortunate emphasis. OBJECTIVE: Since the literature investigating the development of gender identity and gender orientation has not only increased, but also polarized, it is timely to look at the scientific exchange of ideas and debates among the differing positions. METHOD: Exploring the significance of genetic, biological and social factors involved in the development of gender identity and gender orientation based on international literature data. RESULTS: Based on the current state of science it can be concluded that, in addition to the indisputably marked genetic-biological factors, education and social patterns, as well as the extremely complex environmental and media-related influence with its variable intensity and diverse emotional content also play a significant role in the psychosexual development. This is supported, among other observations, by the data indicating that homoerotic behavior is more common in people raised by same-sex couples. CONCLUSION: As psychosexual development is determined jointly by both genetic-biological and social factors (like education, media etc), belonging to a sexual minority group is not a choice, not the result of a personal decision. Therefore, any kind of discrimination in this regard is unacceptable. Further scientific studies are necessary to answer a large number of questions that still remain open.

Comparative serum proteomic analysis of a selected protein panel in individuals with schizophrenia and bipolar disorder and the impact of genetic risk burden on serum proteomic profiles.

The diagnostic criteria for schizophrenia (SCZ) and bipolar disorder (BD) are based on clinical assessments of symptoms. In this pilot study, we applied high-throughput antibody-based protein profiling to serum samples of healthy controls and individuals with SCZ and BD with the aim of identifying differentially expressed proteins in these disorders. Moreover, we explored the influence of polygenic burden for SCZ and BD on the serum levels of these proteins. Serum samples from 113 individuals with SCZ and 125 with BD from the PsyCourse Study and from 44 healthy controls were analyzed by using a set of 155 antibodies in an antibody-based assay targeting a selected panel of 95 proteins. For the cases, genotyping and imputation were conducted for DNA samples and SCZ and BD polygenic risk scores (PRS) were calculated. Univariate linear and logistic models were used for association analyses. The comparison between SCZ and BD revealed two serum proteins that were significantly elevated in BD after multiple testing adjustment: "complement C9" and "Interleukin 1 Receptor Accessory Protein". Moreover, the first principal component of variance in the proteomics dataset differed significantly between SCZ and BD. After multiple testing correction, SCZ-PRS, BD-PRS, and SCZ-vs-BD-PRS were not significantly associated with the levels of the individual proteins or the values of the proteome principal components indicating no detectable genetic effects. Overall, our findings contribute to the evidence suggesting that the analysis of circulating proteins could lead to the identification of distinctive biomarkers for SCZ and BD. Our investigation warrants replication in large-scale studies to confirm these findings.

Biobanking in everyday clinical practice in psychiatry-The Munich Mental Health Biobank.

Translational research on complex, multifactorial mental health disorders, such as bipolar disorder, major depressive disorder, schizophrenia, and substance use disorders requires databases with large-scale, harmonized, and integrated real-world and research data. The Munich Mental Health Biobank (MMHB) is a mental health-specific biobank that was established in 2019 to collect, store, connect, and supply such high-quality phenotypic data and biosamples from patients and study participants, including healthy controls, recruited at the Department of Psychiatry and Psychotherapy (DPP) and the Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital of the Ludwig-Maximilians-University (LMU), Munich, Germany. Participants are asked to complete a questionnaire that assesses sociodemographic and cross-diagnostic clinical information, provide blood samples, and grant access to their existing medical records. The generated data and biosamples are available to both academic and industry researchers. In this manuscript, we outline the workflow and infrastructure of the MMHB, describe the clinical characteristics and representativeness of the sample collected so far, and reveal future plans for expansion and application. As of 31 October 2021, the MMHB contains a continuously growing set of data from 578 patients and 104 healthy controls (46.37% women; median age, 38.31 years). The five most common mental health diagnoses in the MMHB are recurrent depressive disorder (38.78%; ICD-10: F33), alcohol-related disorders (19.88%; ICD-10: F10), schizophrenia (19.69%; ICD-10: F20), depressive episode (15.94%; ICD-10: F32), and personality disorders (13.78%; ICD-10: F60). Compared with the average patient treated at the recruiting hospitals, MMHB participants have significantly more mental health-related contacts, less severe symptoms, and a higher level of functioning. The distribution of diagnoses is also markedly different in MMHB participants compared with individuals who did not participate in the biobank. After establishing the necessary infrastructure and initiating recruitment, the major tasks for the next phase of the MMHB project are to improve the pace of participant enrollment, diversify the sociodemographic and diagnostic characteristics of the sample, and improve the utilization of real-world data generated in routine clinical practice.

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.

Temporal Speech Parameters Detect Mild Cognitive Impairment in Different Languages: Validation and Comparison of the Speech-GAP Test® in English and Hungarian.

BACKGROUND: The development of automatic speech recognition (ASR) technology allows the analysis of temporal (time-based) speech parameters characteristic of mild cognitive impairment (MCI). However, no information has been available on whether the analysis of spontaneous speech can be used with the same efficiency in different language environments. OBJECTIVE: The main goal of this international pilot study is to address the question of whether the Speech-Gap Test® (S-GAP Test®), previously tested in the Hungarian language, is appropriate for and applicable to the recognition of MCI in other languages such as English. METHODS: After an initial screening of 88 individuals, English-speaking (n = 33) and Hungarianspeaking (n = 33) participants were classified as having MCI or as healthy controls (HC) based on Petersen's criteria. The speech of each participant was recorded via a spontaneous speech task. Fifteen temporal parameters were determined and calculated through ASR. RESULTS: Seven temporal parameters in the English-speaking sample and 5 in the Hungarian-speaking sample showed significant differences between the MCI and the HC groups. Receiver operating characteristics (ROC) analysis clearly distinguished the English-speaking MCI cases from the HC group based on speech tempo and articulation tempo with 100% sensitivity, and on three more temporal parameters with high sensitivity (85.7%). In the Hungarian-speaking sample, the ROC analysis showed similar sensitivity rates (92.3%). CONCLUSION: The results of this study in different native-speaking populations suggest that changes in acoustic parameters detected by the S-GAP Test® might be present across different languages.

Stability over time of scores on psychiatric rating scales, questionnaires and cognitive tests in healthy controls.

BACKGROUND: 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. AIMS: 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. METHOD: 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. RESULTS: 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. CONCLUSIONS: 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.