Neuropsychological and brain structural alterations in emerging psychosis

Despite the growing interest in personally tailored interventions in medicine and health care, it is not possible to reach sufficient accuracy in the prediction of psychosis to date. Many factors are associated with transition to psychosis, such as neuropsychological impairments and structural alterations of the brain that have been shown to predate the onset of frank psychosis. However, the different disease trajectories male and female patients' experience may contribute to the mixed picture representing emerging psychosis. The prospective FePsy (Früherkennung von Psychosen) study was a project aiming to improve the early detection and intervention of psychosis through multilevel assessment. The in the following described articles are based on data assessed within the FePsy study. In the first article, structural equation modelling and latent growth curve modelling were used to evaluate verbal learning and memory (VLM) performance between at-risk mental state (ARMS) and first episode psychosis (FEP) patients and healthy controls (HC). In line with our hypothesis, results indicated a worse performance of FEP compared to ARMS and HC and a performance of ARMS intermediate to those two groups. Since these differences were more pronounced in the slope than in the intercept of the learning curve, our results indicated that the verbal learning rate tends to be more impaired than attentional processes in both ARMS and FEP patients. In the second article we investigated whether VLM performance is associated with subcortical brain volumes. A significant negative association between amygdala and pallidum volume and attention span was found in ARMS and FEP patients combined, which however did not withstand correction for multiple testing. Although VLM is among the most impaired cognitive domains in emerging psychosis, the deficits in this domain seem not to necessarily stem from alterations in subcortical structures. In the third article, we investigated whether subcortical brain volumes are dependent on sex. Men presented with larger total brain volume and smaller caudate and hippocampus volumes than women independent of diagnostic group. These analyses confirmed previously described patterns of sexual dimorphism in total brain and caudate volume that are equally present in ARMS and FEP patients as well as HC. The only structure affected by reversed sexual dimorphism was the hippocampus (i.e. women showing higher volumes than men). In conclusion, neuropsychological impairments in terms of VLM and subcortical brain structural alterations are present in emerging psychosis. However, subcortical volumes do not seem to be affected by altered sexual dimorphism and may thus not contribute to an effective prediction modelling of transition to psychosis

Chondrocyte Hypertrophy in Osteoarthritis: Mechanistic Studies and Models for the Identification of New Therapeutic Strategies

Articular cartilage shows limited self-healing ability owing to its low cellularity and avascularity. Untreated cartilage defects display an increased propensity to degenerate, leading to osteoarthritis (OA). During OA progression, articular chondrocytes are subjected to significant alterations in gene expression and phenotype, including a shift towards a hypertrophic-like state (with the expression of collagen type X, matrix metalloproteinases-13, and alkaline phosphatase) analogous to what eventuates during endochondral ossification. Present OA management strategies focus, however, exclusively on cartilage inflammation and degradation. A better understanding of the hypertrophic chondrocyte phenotype in OA might give new insights into its pathogenesis, suggesting potential disease-modifying therapeutic approaches. Recent developments in the field of cellular/molecular biology and tissue engineering proceeded in the direction of contrasting the onset of this hypertrophic phenotype, but knowledge gaps in the cause–effect of these processes are still present. In this review we will highlight the possible advantages and drawbacks of using this approach as a therapeutic strategy while focusing on the experimental models necessary for a better understanding of the phenomenon. Specifically, we will discuss in brief the cellular signaling pathways associated with the onset of a hypertrophic phenotype in chondrocytes during the progression of OA and will analyze in depth the advantages and disadvantages of various models that have been used to mimic it. Afterwards, we will present the strategies developed and proposed to impede chondrocyte hypertrophy and cartilage matrix mineralization/calcification. Finally, we will examine the future perspectives of OA therapeutic strategies

Acute Effects of Methylphenidate, Modafinil, and MDMA on Negative Emotion Processing

Stimulants such as methylphenidate and modafinil are frequently used as cognitive enhancers in healthy people, whereas 3,4-methylenedioxymethamphetamine (ecstasy) is proposed to enhance mood and empathy in healthy subjects. However, comparative data on the effects of methylphenidate and modafinil on negative emotions in healthy subjects have been partially missing. The aim of this study was to compare the acute effects of methylphenidate and modafinil on the neural correlates of fearful face processing using 3,4-methylenedioxymethamphetamine as a positive control.; Using a double-blind, within-subject, placebo-controlled, cross-over design, 60 mg methylphenidate, 600 mg modafinil, and 125 mg 3,4-methylenedioxymethamphetamine were administrated to 22 healthy subjects while performing an event-related fMRI task to assess brain activation in response to fearful faces. Negative mood states were assessed with the State-Trait Anxiety Inventory and subjective ratings.; Relative to placebo, modafinil, but not methylphenidate or 3,4-methylenedioxymethamphetamine, increased brain activation within a limbic-cortical-striatal-pallidal-thalamic circuit during fearful face processing. Modafinil but not methylphenidate also increased amygdala responses to fearful faces compared with 3,4-methylenedioxymethamphetamine. Furthermore, activation in the middle and inferior frontal gyrus in response to fearful faces correlated positively with subjective feelings of fearfulness and depressiveness after modafinil administration.; Despite the cognitive enhancement effects of 600 mg modafinil in healthy people, potential adverse effects on emotion processing should be considered

The relationship between negative symptoms and cognitive functioning in patients at clinical high risk for psychosis

Negative symptoms and neurocognitive performance have been reported to be negatively associated in patients with emerging psychosis. However, most previous studies focused on patients with frank psychosis and did not differentiate between subdomains of negative symptoms. Hence, we aimed to elucidate the specific relationship between negative symptoms and cognitive functioning in patients at clinical high risk (CHR) for psychosis. Data from 154 CHR patients collected within the prospective Früherkennung von Psychosen (FePsy) study were analyzed. Negative symptoms were assessed with the Scale for the Assessment of Negative Symptoms (SANS) and cognitive functioning with an extensive neuropsychological test battery. Regression analyses revealed significant negative associations between negative symptoms and cognitive functioning, particularly in the domains of nonverbal intelligence and verbal fluency. When analyzing each negative symptom domain separately, alogia and asociality/anhedonia were significantly negatively associated with nonverbal intelligence and alogia additionally with verbal fluency. Overall, our results in CHR patients are similar to those reported in patients with frank psychosis. The strong negative association between verbal fluency and negative symptoms may be indicative of an overlap between these constructs. Verbal fluency might have a strong influence on the clinical impression of negative symptoms (particularly alogia) and vice versa

Evaluating verbal learning and memory in patients with an at-risk mental state or first episode psychosis using structural equation modelling

Verbal learning and memory are impaired not only in patients with a first episode of psychosis (FEP) but also-to a lower extent-in those with an at-risk mental state for psychosis (ARMS). However, little is known about the specific nature of these impairments. Hence, we aimed to study learning and memory processes in ARMS and FEP patients by making use of structural equation modelling.; Verbal learning was assessed with the California Verbal Learning Test (CVLT) in 98 FEP patients, 126 ARMS patients and 68 healthy controls (HC) as part of the Basel early detection of psychosis (FePsy) study. The four-factorial CFA model of Donders was used to estimate test performance on latent variables of the CVLT and growth curve analysis was used to model the learning curve. The latter allows disentangling initial recall, which is strongly determined by attentional processes, from the learning rate.; The CFA model revealed that ARMS and FEP patients were impaired in Attention Span, Learning Efficiency and Delayed Memory and that FEP patients were additionally impaired in Inaccurate Memory. Additionally, ARMS-NT, but not ARMS-T, performed significantly worse than HC on Learning Efficiency. The growth curve model indicated that FEP patients were impaired in both initial recall and learning rate and that ARMS patients were only impaired in the learning rate.; Since impairments were more pronounced in the learning rate than the initial recall, our results suggest that the lower scores in the CVLT reported in previous studies are more strongly driven by impairments in the rate of learning than by attentional processes

Sexually dimorphic subcortical brain volumes in emerging psychosis

In schizophrenic psychoses, the normal sexual dimorphism of the brain has been shown to be disrupted or even reversed. Little is known, however, at what time point in emerging psychosis this occurs. We have therefore examined, if these alterations are already present in the at-risk mental state (ARMS) for psychosis and in first episode psychosis (FEP) patients.; Data from 65 ARMS (48 (73.8%) male; age=25.1±6.32) and 50 FEP (37 (74%) male; age=27±6.56) patients were compared to those of 70 healthy controls (HC; 27 (38.6%) male; age=26±4.97). Structural T1-weighted images were acquired using a 3 Tesla magnetic resonance imaging (MRI) scanner. Linear mixed effects models were used to investigate whether subcortical brain volumes are dependent on sex.; We found men to have larger total brain volumes (p<0.001), and smaller bilateral caudate (p=0.008) and hippocampus volume (p<0.001) than women across all three groups. Older subjects had more GM and WM volume than younger subjects. No significant sex×group interaction was found.; In emerging psychosis there still seem to exist patterns of normal sexual dimorphism in total brain and caudate volume. The only structure affected by reversed sexual dimorphism was the hippocampus, with women showing larger volumes than men even in HC. Thus, we conclude that subcortical volumes may not be primarily affected by disrupted sexual dimorphism in emerging psychosis

Can neuropsychological testing facilitate differential diagnosis between at-risk mental state (ARMS) for psychosis and adult attention-deficit/hyperactivity disorder (ADHD)?

Background: Patients with an at-risk mental state (ARMS) for psychosis and patients with attention-deficit/hyperactivity disorder (ADHD) have many overlapping signs and symptoms and hence can be difficult to differentiate clinically. The aim of this study was to investigate whether the differential diagnosis between ARMS and adult ADHD could be improved by neuropsychological testing. Methods 168 ARMS patients, 123 adult ADHD patients and 109 healthy controls (HC) were recruited via specialized clinics of the University of Basel Psychiatric Hospital. Sustained attention and impulsivity were tested with the Continuous Performance Test, verbal learning and memory with the California Verbal Learning Test, and problem solving abilities with the Tower of Hanoi Task. Group differences in neuropsychological performance were analyzed using generalized linear models. Furthermore, to investigate whether adult ADHD and ARMS can be correctly classified based on the pattern of cognitive deficits, machine learning (i.e. random forests) was applied. Results Compared to HC, both patient groups showed deficits in attention and impulsivity and verbal learning and memory. However, in adult ADHD patients the deficits were comparatively larger. Accordingly, a machine learning model predicted group membership based on the individual neurocognitive performance profile with good accuracy (AUC = 0.82). Conclusions Our results are in line with current meta-analyses reporting that impairments in the domains of attention and verbal learning are of medium effect size in adult ADHD and of small effect size in ARMS patients and suggest that measures of these domains can be exploited to improve the differential diagnosis between adult ADHD and ARMS patients

Cortical brain abnormalities in 4474 individuals with schizophrenia and 5098 control subjects via the enhancing neuro Imaging genetics through meta analysis (ENIGMA) Consortium

BACKGROUND: The profile of cortical neuroanatomical abnormalities in schizophrenia is not fully understood, despite hundreds of published structural brain imaging studies. This study presents the first meta-analysis of cortical thickness and surface area abnormalities in schizophrenia conducted by the ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) Schizophrenia Working Group. METHODS: The study included data from 4474 individuals with schizophrenia (mean age, 32.3 years; range, 11-78 years; 66% male) and 5098 healthy volunteers (mean age, 32.8 years; range, 10-87 years; 53% male) assessed with standardized methods at 39 centers worldwide. RESULTS: Compared with healthy volunteers, individuals with schizophrenia have widespread thinner cortex (left/right hemisphere: Cohen's d = -0.530/-0.516) and smaller surface area (left/right hemisphere: Cohen's d = -0.251/-0.254), with the largest effect sizes for both in frontal and temporal lobe regions. Regional group differences in cortical thickness remained significant when statistically controlling for global cortical thickness, suggesting regional specificity. In contrast, effects for cortical surface area appear global. Case-control, negative, cortical thickness effect sizes were two to three times larger in individuals receiving antipsychotic medication relative to unmedicated individuals. Negative correlations between age and bilateral temporal pole thickness were stronger in individuals with schizophrenia than in healthy volunteers. Regional cortical thickness showed significant negative correlations with normalized medication dose, symptom severity, and duration of illness and positive correlations with age at onset. CONCLUSIONS: The findings indicate that the ENIGMA meta-analysis approach can achieve robust findings in clinical neuroscience studies; also, medication effects should be taken into account in future genetic association studies of cortical thickness in schizophrenia

Multimodal Machine Learning Workflows for Prediction of Psychosis in Patients With Clinical High-Risk Syndromes and Recent-Onset Depression

Importance Diverse models have been developed to predict psychosis in patients with clinical high-risk (CHR) states. Whether prediction can be improved by efficiently combining clinical and biological models and by broadening the risk spectrum to young patients with depressive syndromes remains unclear. Objectives To evaluate whether psychosis transition can be predicted in patients with CHR or recent-onset depression (ROD) using multimodal machine learning that optimally integrates clinical and neurocognitive data, structural magnetic resonance imaging (sMRI), and polygenic risk scores (PRS) for schizophrenia; to assess models' geographic generalizability; to test and integrate clinicians' predictions; and to maximize clinical utility by building a sequential prognostic system. Design, Setting, and Participants This multisite, longitudinal prognostic study performed in 7 academic early recognition services in 5 European countries followed up patients with CHR syndromes or ROD and healthy volunteers. The referred sample of 167 patients with CHR syndromes and 167 with ROD was recruited from February 1, 2014, to May 31, 2017, of whom 26 (23 with CHR syndromes and 3 with ROD) developed psychosis. Patients with 18-month follow-up (n = 246) were used for model training and leave-one-site-out cross-validation. The remaining 88 patients with nontransition served as the validation of model specificity. Three hundred thirty-four healthy volunteers provided a normative sample for prognostic signature evaluation. Three independent Swiss projects contributed a further 45 cases with psychosis transition and 600 with nontransition for the external validation of clinical-neurocognitive, sMRI-based, and combined models. Data were analyzed from January 1, 2019, to March 31, 2020. Main Outcomes and Measures Accuracy and generalizability of prognostic systems. Results A total of 668 individuals (334 patients and 334 controls) were included in the analysis (mean [SD] age, 25.1 [5.8] years; 354 [53.0%] female and 314 [47.0%] male). Clinicians attained a balanced accuracy of 73.2% by effectively ruling out (specificity, 84.9%) but ineffectively ruling in (sensitivity, 61.5%) psychosis transition. In contrast, algorithms showed high sensitivity (76.0%-88.0%) but low specificity (53.5%-66.8%). A cybernetic risk calculator combining all algorithmic and human components predicted psychosis with a balanced accuracy of 85.5% (sensitivity, 84.6%; specificity, 86.4%). In comparison, an optimal prognostic workflow produced a balanced accuracy of 85.9% (sensitivity, 84.6%; specificity, 87.3%) at a much lower diagnostic burden by sequentially integrating clinical-neurocognitive, expert-based, PRS-based, and sMRI-based risk estimates as needed for the given patient. Findings were supported by good external validation results. Conclusions and RelevanceThese findings suggest that psychosis transition can be predicted in a broader risk spectrum by sequentially integrating algorithms' and clinicians' risk estimates. For clinical translation, the proposed workflow should undergo large-scale international validation.Question Can a transition to psychosis be predicted in patients with clinical high-risk states or recent-onset depression by optimally integrating clinical, neurocognitive, neuroimaging, and genetic information with clinicians' prognostic estimates? Findings In this prognostic study of 334 patients and 334 control individuals, machine learning models sequentially combining clinical and biological data with clinicians' estimates correctly predicted disease transitions in 85.9% of cases across geographically distinct patient populations. The clinicians' lack of prognostic sensitivity, as measured by a false-negative rate of 38.5%, was reduced to 15.4% by the sequential prognostic model. Meaning These findings suggest that an individualized prognostic workflow integrating artificial and human intelligence may facilitate the personalized prevention of psychosis in young patients with clinical high-risk syndromes or recent-onset depression.</p