Alterations of Functional Connectivity Dynamics in Affective and Psychotic Disorders

BACKGROUND

Psychosis and depression patients exhibit widespread neurobiological abnormalities. The analysis of dynamic functional connectivity (dFC), allows for the detection of changes in complex brain activity patterns, providing insights into common and unique processes underlying these disorders.

METHODS

In the present study, we report the analysis of dFC in a large patient sample including 127 clinical high-risk patients (CHR), 142 recent-onset psychosis (ROP) patients, 134 recent-onset depression (ROD) patients, and 256 healthy controls (HC). A sliding window-based technique was used to calculate the time-dependent FC in resting-state MRI data, followed by clustering to reveal recurrent FC states in each diagnostic group.

RESULTS

We identified five unique FC states, which could be identified in all groups with high consistency (rmean = 0.889, sd = 0.116). Analysis of dynamic parameters of these states showed a characteristic increase in the lifetime and frequency of a weakly-connected FC state in ROD patients (p < 0.0005) compared to most other groups, and a common increase in the lifetime of a FC state characterised by high sensorimotor and cingulo-opercular connectivities in all patient groups compared to the HC group (p < 0.0002). Canonical correlation analysis revealed a mode which exhibited significant correlations between dFC parameters and clinical variables (r = 0.617, p < 0.0029), which was associated with positive psychosis symptom severity and several dFC parameters.

CONCLUSIONS

Our findings indicate diagnosis-specific alterations of dFC and underline the potential of dynamic analysis to characterize disorders such as depression, psychosis and clinical risk states.

Transdiagnostic subgroups of cognitive impairment in early affective and psychotic illness

Cognitively impaired and spared patient subgroups were identified in psychosis and depression, and in clinical high-risk for psychosis (CHR). Studies suggest differences in underlying brain structural and functional characteristics. It is unclear whether cognitive subgroups are transdiagnostic phenomena in early stages of psychotic and affective disorder which can be validated on the neural level. Patients with recent-onset psychosis (ROP; N = 140; female = 54), recent-onset depression (ROD; N = 130; female = 73), CHR (N = 128; female = 61) and healthy controls (HC; N = 270; female = 165) were recruited through the multi-site study PRONIA. The transdiagnostic sample and individual study groups were clustered into subgroups based on their performance in eight cognitive domains and characterized by gray matter volume (sMRI) and resting-state functional connectivity (rsFC) using support vector machine (SVM) classification. We identified an impaired subgroup (NROP = 79, NROD = 30, NCHR = 37) showing cognitive impairment in executive functioning, working memory, processing speed and verbal learning (all p < 0.001). A spared subgroup (NROP = 61, NROD = 100, NCHR = 91) performed comparable to HC. Single-disease subgroups indicated that cognitive impairment is stronger pronounced in impaired ROP compared to impaired ROD and CHR. Subgroups in ROP and ROD showed specific symptom- and functioning-patterns. rsFC showed superior accuracy compared to sMRI in differentiating transdiagnostic subgroups from HC (BACimpaired = 58.5%; BACspared = 61.7%, both: p < 0.01). Cognitive findings were validated in the PRONIA replication sample (N = 409). Individual cognitive subgroups in ROP, ROD and CHR are more informative than transdiagnostic subgroups as they map onto individual cognitive impairment and specific functioning- and symptom-patterns which show limited overlap in sMRI and rsFC. CLINICAL TRIAL REGISTRY NAME: German Clinical Trials Register (DRKS). Clinical trial registry URL: https://www.drks.de/drks_web/ . Clinical trial registry number: DRKS00005042.

A multivariate cognitive approach to predict social functioning in recent onset psychosis in response to computerized cognitive training

Clinical and neuroimaging data has been increasingly used in recent years to disentangle heterogeneity of treatment response to cognitive training (CT) and predict which individuals may achieve the highest benefits. CT has small to medium effects on improving cognitive and social functioning in recent onset psychosis (ROP) patients, who show the most profound cognitive and social functioning deficits among psychiatric patients. We employed multivariate pattern analysis (MVPA) to investigate the potential of cognitive data to predict social functioning improvement in response to 10 h of CT in patients with ROP. A support vector machine (SVM) classifier was trained on the naturalistic data of the Personalized Prognostic Tools for Early Psychosis Management (PRONIA) study sample to predict functioning in an independent sample of 70 ROP patients using baseline cognitive data. PRONIA is a part of a FP7 EU grant program that involved 7 sites across 5 European countries, designed and conducted with the main aim of identifying (bio)markers associated with an enhanced risk of developing psychosis in order to improve early detection and prognosis. Social functioning was predicted with a balanced accuracy (BAC) of 66.4% (Sensitivity 78.8%; Specificity 54.1%; PPV 60.5%; NPV 74.1%; AUC 0.64; P = 0.01). The most frequently selected cognitive features (mean feature weights > ± 0.2) included the (1) correct number of symbol matchings within the Digit Symbol Substitution Test, (2) the number of distracting stimuli leading to an error within 300 and 200 trials in the Continuous Performance Test and (3) the dynamics of verbal fluency between 15 and 30 s within the Verbal Fluency Test, phonetic part. Next, the SVM classifier generated on the PRONIA sample was applied to the intervention sample, that obtained 54 ROP patients who were randomly assigned to a social cognitive training (SCT) or treatment as usual (TAU) group and dichotomized into good (GF-S ≥ 7) and poor (GF-S < 7) functioning patients based on their level of Global Functioning-Social (GF-S) score at follow-up (FU). By applying the initial PRONIA classifier, using out-of-sample cross-validation (OOCV) to the sample of ROP patients who have undergone the CT intervention, a BAC of 59.3% (Sensitivity 70.4%; Specificity 48.1%; PPV 57.6%; NPV 61.9%; AUC 0.63) was achieved at T0 and a BAC of 64.8% (Sensitivity 66.7%; Specificity 63.0%; PPV 64.3%; NPV 65.4%; AUC 0.66) at FU. After SCT intervention, a significant improvement in predicted social functioning values was observed in the SCT compared to TAU group (P ≤0.05; ES[Cohens' d] = 0.18). Due to a small sample size and modest variance of social functioning of the intervention sample it was not feasible to predict individual response to SCT in the current study. Our findings suggest that the use of baseline cognitive data could provide a robust individual estimate of future social functioning, while prediction of individual response to SCT using cognitive data that can be generated in the routine patient care remains to be addressed in large-scale cognitive training trials.

Prevalence of cognitive impairments and strengths in the early course of psychosis and depression

BACKGROUND

Studies investigating cognitive impairments in psychosis and depression have typically compared the average performance of the clinical group against healthy controls (HC), and do not report on the actual prevalence of cognitive impairments or strengths within these clinical groups. This information is essential so that clinical services can provide adequate resources to supporting cognitive functioning. Thus, we investigated this prevalence in individuals in the early course of psychosis or depression.

METHODS

A comprehensive cognitive test battery comprising 12 tests was completed by 1286 individuals aged 15-41 (mean age 25.07, s.d. 5.88) from the PRONIA study at baseline: HC (N = 454), clinical high risk for psychosis (CHR; N = 270), recent-onset depression (ROD; N = 267), and recent-onset psychosis (ROP; N = 295). Z-scores were calculated to estimate the prevalence of moderate or severe deficits or strengths (>2 s.d. or 1-2 s.d. below or above HC, respectively) for each cognitive test.

RESULTS

Impairment in at least two cognitive tests was as follows: ROP (88.3% moderately, 45.1% severely impaired), CHR (71.2% moderately, 22.4% severely impaired), ROD (61.6% moderately, 16.2% severely impaired). Across clinical groups, impairments were most prevalent in tests of working memory, processing speed, and verbal learning. Above average performance (>1 s.d.) in at least two tests was present for 40.5% ROD, 36.1% CHR, 16.1% ROP, and was >2 SDs in 1.8% ROD, 1.4% CHR, and 0% ROP.

CONCLUSIONS

These findings suggest that interventions should be tailored to the individual, with working memory, processing speed, and verbal learning likely to be important transdiagnostic targets.

Neurocognitive skills and vulnerability for psychosis in depression and across the psychotic spectrum: findings from the PRONIA Consortium

BACKGROUND

Neurocognitive deficits are a core feature of psychosis and depression. Despite commonalities in cognitive alterations, it remains unclear if and how the cognitive deficits in patients at clinical high risk for psychosis (CHR) and those with recent-onset psychosis (ROP) are distinct from those seen in recent-onset depression (ROD).

AIMS

This study was carried out within the European project 'Personalized Prognostic Tools for Early Psychosis Management', and aimed to characterise the cognitive profiles of patients with psychosis or depression.

METHOD

We examined cognitive profiles for patients with ROP (n = 105), patients with ROD (n = 123), patients at CHR (n = 116) and healthy controls (n = 372) across seven sites in five European countries. Confirmatory factor analysis identified four cognitive factors independent of gender, education and site: speed of processing, attention and working memory, verbal learning and spatial learning.

RESULTS

Patients with ROP performed worse than healthy controls in all four domains (P < 0.001), whereas performance of patients with ROD was not affected (P > 0.05). Patients at CHR performed worse than healthy controls in speed of processing (P = 0.001) and spatial learning (P = 0.003), but better than patients with ROP across all cognitive domains (all P ≤ 0.01). CHR and ROD groups did not significantly differ in any cognitive domain. These findings were independent of comorbid depressive symptoms, substance consumption and illness duration.

CONCLUSIONS

These results show that neurocognitive abilities are affected in CHR and ROP, whereas ROD seems spared. Although our findings may support the notion that those at CHR have a specific vulnerability to psychosis, future studies investigating broader transdiagnostic risk cohorts in longitudinal designs are needed.

Ecological momentary assessment (EMA) combined with unsupervised machine learning shows sensitivity to identify individuals in potential need for psychiatric assessment

Ecological momentary assessment (EMA), a structured diary assessment technique, has shown feasibility to capture psychotic(-like) symptoms across different study groups. We investigated whether EMA combined with unsupervised machine learning can distinguish groups on the continuum of genetic risk toward psychotic illness and identify individuals with need for extended healthcare. Individuals with psychotic disorder (PD, N = 55), healthy individuals (HC, N = 25) and HC with first-degree relatives with psychosis (RE, N = 20) were assessed at two sites over 7 days using EMA. Cluster analysis determined subgroups based on similarities in longitudinal trajectories of psychotic symptom ratings in EMA, agnostic of study group assignment. Psychotic symptom ratings were calculated as average of items related to hallucinations and paranoid ideas. Prior to EMA we assessed symptoms using the Positive and Negative Syndrome Scale (PANSS) and the Community Assessment of Psychic Experience (CAPE) to characterize the EMA subgroups. We identified two clusters with distinct longitudinal EMA characteristics. Cluster 1 (NPD = 12, NRE = 1, NHC = 2) showed higher mean EMA symptom ratings as compared to cluster 2 (NPD = 43, NRE = 19, NHC = 23) (p < 0.001). Cluster 1 showed a higher burden on negative (p < 0.05) and positive (p < 0.05) psychotic symptoms in cross-sectional PANSS and CAPE ratings than cluster 2. Findings indicate a separation of PD with high symptom burden (cluster 1) from PD with healthy-like rating patterns grouping together with HC and RE (cluster 2). Individuals in cluster 1 might particularly profit from exchange with a clinician underlining the idea of EMA as clinical monitoring tool.

The non-specific nature of mental health and structural brain outcomes following childhood trauma

BACKGROUND

Childhood trauma (CT) is associated with an increased risk of mental health disorders; however, it is unknown whether this represents a diagnosis-specific risk factor for specific psychopathology mediated by structural brain changes. Our aim was to explore whether (i) a predictive CT pattern for transdiagnostic psychopathology exists, and whether (ii) CT can differentiate between distinct diagnosis-dependent psychopathology. Furthermore, we aimed to identify the association between CT, psychopathology and brain structure.

METHODS

We used multivariate pattern analysis in data from 643 participants of the Personalised Prognostic Tools for Early Psychosis Management study (PRONIA), including healthy controls (HC), recent onset psychosis (ROP), recent onset depression (ROD), and patients clinically at high-risk for psychosis (CHR). Participants completed structured interviews and self-report measures including the Childhood Trauma Questionnaire, SCID diagnostic interview, BDI-II, PANSS, Schizophrenia Proneness Instrument, Structured Interview for Prodromal Symptoms and structural MRI, analyzed by voxel-based morphometry.

RESULTS

(i) Patients and HC could be distinguished by their CT pattern with a reasonable precision [balanced accuracy of 71.2% (sensitivity = 72.1%, specificity = 70.4%, p ≤ 0.001]. (ii) Subdomains 'emotional neglect' and 'emotional abuse' were most predictive for CHR and ROP, while in ROD 'physical abuse' and 'sexual abuse' were most important. The CT pattern was significantly associated with the severity of depressive symptoms in ROD, ROP, and CHR, as well as with the PANSS total and negative domain scores in the CHR patients. No associations between group-separating CT patterns and brain structure were found.

CONCLUSIONS

These results indicate that CT poses a transdiagnostic risk factor for mental health disorders, possibly related to depressive symptoms. While differences in the quality of CT exposure exist, diagnostic differentiation was not possible suggesting a multi-factorial pathogenesis.

Coffee consumption and cardiovascular health in the general population

Background

Coffee, next to water the most widespread beverage, is attributed both harmful and protective characteristics concerning cardiovascular health. This study aimed to evaluate associations of coffee consumption with cardiac biomarkers, echocardiographic, and electrocardiographic parameters as well as major cardiovascular diseases.

Methods and results

We performed a cross-sectional analysis of 9,009 participants a large German population-based cohort study, enrolled between 2016 and 2018 median age 63 [IQR: 55; 69] years. Coffee consumption was classified into three groups: &lt;3 cups/day (low), 3–4 cups/day (moderate), &gt;4 cups/day (high). In linear regression analyses adjusted for age, sex, body mass index, diabetes, hypertension, and smoking, moderate and high coffee consumption were associated with LDL-cholesterol (β=2.08; 95% CI: 0.14, 4.03, p=0.036; β=5.69; 95% CI: 2.91, 8.47; p&lt;0.001). Moderate and high coffee consumption were negatively associated with systolic (β=−1.6; 95% CI: −2.66, −0.54; p=0.003; β=−2.63; 95% CI: −4.15, −1.12; p=0.001) and diastolic blood pressure (β=−0.8; 95% CI: −1.38, −0.22; p=0.007; β=1.28; 95% CI: −2.11, −0.45; p=0.002). Different levels of coffee consumption did neither correlate with any investigated electrocardiographic or echocardiographic parameter nor with prevalent major cardiovascular diseases, including prior myocardial infarction and heart failure.

Conclusions

In this cross-sectional analysis, moderate and high coffee consumption was positively associated with LDL-cholesterol and negatively associated with systolic and diastolic blood pressure. However, major cardiovascular diseases including heart failure and its diagnostic precursors were not associated with coffee consumption, connoting a neutral role of coffee in the context of cardiovascular health.

Funding Acknowledgement

Type of funding sources: Foundation. Main funding source(s): Deutsche Forschungsgemeinschaft [Grant Number TH1106/5-1; AA93/2-1]The Foundation Leducq [Grant Number 16 CVD 03]

Neurobiologically Based Stratification of Recent-Onset Depression and Psychosis: Identification of Two Distinct Transdiagnostic Phenotypes

BACKGROUND

Identifying neurobiologically based transdiagnostic categories of depression and psychosis may elucidate heterogeneity and provide better candidates for predictive modeling. We aimed to identify clusters across patients with recent-onset depression (ROD) and recent-onset psychosis (ROP) based on structural neuroimaging data. We hypothesized that these transdiagnostic clusters would identify patients with poor outcome and allow more accurate prediction of symptomatic remission than traditional diagnostic structures.

METHODS

HYDRA (Heterogeneity through Discriminant Analysis) was trained on whole-brain volumetric measures from 577 participants from the discovery sample of the multisite PRONIA study to identify neurobiologically driven clusters, which were then externally validated in the PRONIA replication sample (n = 404) and three datasets of chronic samples (Centre for Biomedical Research Excellence, n = 146; Mind Clinical Imaging Consortium, n = 202; Munich, n = 470).

RESULTS

The optimal clustering solution was two transdiagnostic clusters (cluster 1: n = 153, 67 ROP, 86 ROD; cluster 2: n = 149, 88 ROP, 61 ROD; adjusted Rand index = 0.618). The two clusters contained both patients with ROP and patients with ROD. One cluster had widespread gray matter volume deficits and more positive, negative, and functional deficits (impaired cluster), and one cluster revealed a more preserved neuroanatomical signature and more core depressive symptomatology (preserved cluster). The clustering solution was internally and externally validated and assessed for clinical utility in predicting 9-month symptomatic remission, outperforming traditional diagnostic structures.

CONCLUSIONS

We identified two transdiagnostic neuroanatomically informed clusters that are clinically and biologically distinct, challenging current diagnostic boundaries in recent-onset mental health disorders. These results may aid understanding of the etiology of poor outcome patients transdiagnostically and improve development of stratified treatments.

Relationships between global functioning and neuropsychological predictors in subjects at high risk of psychosis or with a recent onset of depression

OBJECTIVE

Psychotic disorders are frequently associated with decline in functioning and cognitive difficulties are observed in subjects at clinical high risk (CHR) for psychosis. In this work, we applied automatic approaches to neurocognitive and functioning measures, with the aim of investigating the link between global, social and occupational functioning, and cognition.

METHODS

102 CHR subjects and 110 patients with recent onset depression (ROD) were recruited. Global assessment of functioning (GAF) related to symptoms (GAF-S) and disability (GAF-D). and global functioning social (GF-S) and role (GF-R), at baseline and of the previous month and year, and a set of neurocognitive measures, were used for classification and regression.

RESULTS

Neurocognitive measures related to GF-R at baseline (r = 0.20, p = 0.004), GF-S at present (r = 0.14, p = 0.042) and of the past year (r = 0.19, p = 0.005), for GAF-F of the past month (r = 0.24, p < 0.001) and GAF-D of the past year (r = 0.28, p = 0.002). Classification reached values of balanced accuracy of 61% for GF-R and GAF-D.

CONCLUSION

We found that neurocognition was related to psychosocial functioning. More specifically, a deficit in executive functions was associated to poor social and occupational functioning.

Clinical, Brain, and Multilevel Clustering in Early Psychosis and Affective Stages

Importance

Approaches are needed to stratify individuals in early psychosis stages beyond positive symptom severity to investigate specificity related to affective and normative variation and to validate solutions with premorbid, longitudinal, and genetic risk measures.

Objective

To use machine learning techniques to cluster, compare, and combine subgroup solutions using clinical and brain structural imaging data from early psychosis and depression stages.

Design, Setting, and Participants

A multisite, naturalistic, longitudinal cohort study (10 sites in 5 European countries; including major follow-up intervals at 9 and 18 months) with a referred patient sample of those with clinical high risk for psychosis (CHR-P), recent-onset psychosis (ROP), recent-onset depression (ROD), and healthy controls were recruited between February 1, 2014, to July 1, 2019. Data were analyzed between January 2020 and January 2022.

Main Outcomes and Measures

A nonnegative matrix factorization technique separately decomposed clinical (287 variables) and parcellated brain structural volume (204 gray, white, and cerebrospinal fluid regions) data across CHR-P, ROP, ROD, and healthy controls study groups. Stability criteria determined cluster number using nested cross-validation. Validation targets were compared across subgroup solutions (premorbid, longitudinal, and schizophrenia polygenic risk scores). Multiclass supervised machine learning produced a transferable solution to the validation sample.

Results

There were a total of 749 individuals in the discovery group and 610 individuals in the validation group. Individuals included those with CHR-P (n = 287), ROP (n = 323), ROD (n = 285), and healthy controls (n = 464), The mean (SD) age was 25.1 (5.9) years, and 702 (51.7%) were female. A clinical 4-dimensional solution separated individuals based on positive symptoms, negative symptoms, depression, and functioning, demonstrating associations with all validation targets. Brain clustering revealed a subgroup with distributed brain volume reductions associated with negative symptoms, reduced performance IQ, and increased schizophrenia polygenic risk scores. Multilevel results distinguished between normative and illness-related brain differences. Subgroup results were largely validated in the external sample.

Conclusions and Relevance

The results of this longitudinal cohort study provide stratifications beyond the expression of positive symptoms that cut across illness stages and diagnoses. Clinical results suggest the importance of negative symptoms, depression, and functioning. Brain results suggest substantial overlap across illness stages and normative variation, which may highlight a vulnerability signature independent from specific presentations. Premorbid, longitudinal, and genetic risk validation suggested clinical importance of the subgroups to preventive treatments.

Pattern of predictive features of continued cannabis use in patients with recent-onset psychosis and clinical high-risk for psychosis

Continued cannabis use (CCu) is an important predictor for poor long-term outcomes in psychosis and clinically high-risk patients, but no generalizable model has hitherto been tested for its ability to predict CCu in these vulnerable patient groups. In the current study, we investigated how structured clinical and cognitive assessments and structural magnetic resonance imaging (sMRI) contributed to the prediction of CCu in a group of 109 patients with recent-onset psychosis (ROP). We tested the generalizability of our predictors in 73 patients at clinical high-risk for psychosis (CHR). Here, CCu was defined as any cannabis consumption between baseline and 9-month follow-up, as assessed in structured interviews. All patients reported lifetime cannabis use at baseline. Data from clinical assessment alone correctly classified 73% (p < 0.001) of ROP and 59 % of CHR patients. The classifications of CCu based on sMRI and cognition were non-significant (ps > 0.093), and their addition to the interview-based predictor via stacking did not improve prediction significantly, either in the ROP or CHR groups (ps > 0.065). Lower functioning, specific substance use patterns, urbanicity and a lack of other coping strategies contributed reliably to the prediction of CCu and might thus represent important factors for guiding preventative efforts. Our results suggest that it may be possible to identify by clinical measures those psychosis-spectrum patients at high risk for CCu, potentially allowing to improve clinical care through targeted interventions. However, our model needs further testing in larger samples including more diverse clinical populations before being transferred into clinical practice.

Cognitive Performance and Learning Parameters Predict Response to Working Memory Training in Parkinson's Disease

BACKGROUND

Working memory (WM) training (WMT) is a popular intervention approach against cognitive decline in patients with Parkinson's disease (PD). However, heterogeneity in WM responsiveness suggests that WMT may not be equally efficient for all patients.

OBJECTIVE

The present study aims to evaluate a multivariate model to predict post-intervention verbal WM in patients with PD using a supervised machine learning approach. We test the predictive potential of novel learning parameters derived from the WMT and compare their predictiveness to other more commonly used domains including demographic, clinical, and cognitive data.

METHODS

37 patients with PD (age: 64.09±8.56, 48.6% female, 94.7% Hoehn & Yahr stage 2) participated in a 5-week WMT. Four random forest regression models including 1) cognitive variables only, 2) learning parameters only, 3) both cognitive and learning variables, and 4) the entire set of variables (with additional demographic and clinical data, 'all' model), were built to predict immediate and 3-month-follow-up WM.

RESULT

The 'all' model predicted verbal WM with the lowest root mean square error (RMSE) compared to the other models, at both immediate (RMSE = 0.184; 95% -CI=[0.184;0.185]) and 3-month follow-up (RMSE = 0.216; 95% -CI=[0.215;0.217]). Cognitive baseline parameters were among the most important predictors in the 'all' model. The model combining cognitive and learning parameters significantly outperformed the model solely based on cognitive variables.

CONCLUSION

Commonly assessed demographic, clinical, and cognitive variables provide robust prediction of response to WMT. Nonetheless, inclusion of training-inherent learning parameters further boosts precision of prediction models which in turn may augment training benefits following cognitive interventions in patients with PD.

Epigallocatechin-3-gallate exhibits anti-inflammatory effects in a human interface dermatitis model-implications for therapy

BACKGROUND

Epigallocatechin-3-gallate (EGCG) has been proven effective in treating viral warts. Since anticarcinogenic as well as anti-inflammatory properties are ascribed to the substance, its use has been evaluated in the context of different dermatoses. The effect of EGCG on interface dermatitis (ID), however, has not yet been explored.

OBJECTIVES

In this study, we investigated the effect of EGCG on an epidermal human in vitro model of ID.

METHODS

Via immunohistochemistry, lesional skin of lichen planus patients and healthy skin were analysed concerning the intensity of interferon-associated mediators, CXCL10 and MxA. Epidermal equivalents were stained analogously upon ID-like stimulation and EGCG treatment. Monolayer keratinocytes were treated likewise and supernatants were analysed via ELISA while cells were processed for vitality assay or transcriptomic analysis.

RESULTS

CXCL10 and MxA are strongly expressed in lichen planus lesions and induced in keratinocytes upon ID-like stimulation. EGCG reduces CXCL10 and MxA staining intensity in epidermis equivalents and CXCL10 secretion by keratinocytes upon stimulation. It furthermore minimizes the cytotoxic effect of the stimulus and downregulates a magnitude of typical pro-inflammatory cytokines that are crucial for the perpetuation of ID.

CONCLUSIONS

We provide evidence concerning anti-inflammatory effects of EGCG within a human in vitro model of ID. The capacity to suppress mediators that are centrally involved in disease perpetuation suggests EGCG as a potential topical therapeutic in lichen planus and other autoimmune skin diseases associated with ID.

Novel Gyrification Networks Reveal Links with Psychiatric Risk Factors in Early Illness

Adult gyrification provides a window into coordinated early neurodevelopment when disruptions predispose individuals to psychiatric illness. We hypothesized that the echoes of such disruptions should be observed within structural gyrification networks in early psychiatric illness that would demonstrate associations with developmentally relevant variables rather than specific psychiatric symptoms. We employed a new data-driven method (Orthogonal Projective Non-Negative Matrix Factorization) to delineate novel gyrification-based networks of structural covariance in 308 healthy controls. Gyrification within the networks was then compared to 713 patients with recent onset psychosis or depression, and at clinical high-risk. Associations with diagnosis, symptoms, cognition, and functioning were investigated using linear models. Results demonstrated 18 novel gyrification networks in controls as verified by internal and external validation. Gyrification was reduced in patients in temporal-insular, lateral occipital, and lateral fronto-parietal networks (pFDR < 0.01) and was not moderated by illness group. Higher gyrification was associated with better cognitive performance and lifetime role functioning, but not with symptoms. The findings demonstrated that gyrification can be parsed into novel brain networks that highlight generalized illness effects linked to developmental vulnerability. When combined, our study widens the window into the etiology of psychiatric risk and its expression in adulthood.

Multivariate pattern analysis of brain structure predicts functional outcome after auditory-based cognitive training interventions

Cognitive gains following cognitive training interventions are associated with improved functioning in people with schizophrenia (SCZ). However, considerable inter-individual variability is observed. Here, we evaluate the sensitivity of brain structural features to predict functional response to auditory-based cognitive training (ABCT) at a single-subject level. We employed whole-brain multivariate pattern analysis with support vector machine (SVM) modeling to identify gray matter (GM) patterns that predicted higher vs. lower functioning after 40 h of ABCT at the single-subject level in SCZ patients. The generalization capacity of the SVM model was evaluated by applying the original model through an out-of-sample cross-validation analysis to unseen SCZ patients from an independent validation sample who underwent 50 h of ABCT. The whole-brain GM volume-based pattern classification predicted higher vs. lower functioning at follow-up with a balanced accuracy (BAC) of 69.4% (sensitivity 72.2%, specificity 66.7%) as determined by nested cross-validation. The neuroanatomical model was generalizable to an independent cohort with a BAC of 62.1% (sensitivity 90.9%, specificity 33.3%). In particular, greater baseline GM volumes in regions within superior temporal gyrus, thalamus, anterior cingulate, and cerebellum predicted improved functioning at the single-subject level following ABCT in SCZ participants. The present findings provide a structural MRI fingerprint associated with preserved GM volumes at a single baseline timepoint, which predicted improved functioning following an ABCT intervention, and serve as a model for how to facilitate precision clinical therapies for SCZ based on imaging data, operating at the single-subject level.

A multivariate neuromonitoring approach to neuroplasticity-based computerized cognitive training in recent onset psychosis

Two decades of studies suggest that computerized cognitive training (CCT) has an effect on cognitive improvement and the restoration of brain activity. Nevertheless, individual response to CCT remains heterogenous, and the predictive potential of neuroimaging in gauging response to CCT remains unknown. We employed multivariate pattern analysis (MVPA) on whole-brain resting-state functional connectivity (rsFC) to (neuro)monitor clinical outcome defined as psychosis-likeness change after 10-hours of CCT in recent onset psychosis (ROP) patients. Additionally, we investigated if sensory processing (SP) change during CCT is associated with individual psychosis-likeness change and cognitive gains after CCT. 26 ROP patients were divided into maintainers and improvers based on their SP change during CCT. A support vector machine (SVM) classifier separating 56 healthy controls (HC) from 35 ROP patients using rsFC (balanced accuracy of 65.5%, P < 0.01) was built in an independent sample to create a naturalistic model representing the HC-ROP hyperplane. This model was out-of-sample cross-validated in the ROP patients from the CCT trial to assess associations between rsFC pattern change, cognitive gains and SP during CCT. Patients with intact SP threshold at baseline showed improved attention despite psychosis status on the SVM hyperplane at follow-up (p < 0.05). Contrarily, the attentional gains occurred in the ROP patients who showed impaired SP at baseline only if rsfMRI diagnosis status shifted to the healthy-like side of the SVM continuum. Our results reveal the utility of MVPA for elucidating treatment response neuromarkers based on rsFC-SP change and pave the road to more personalized interventions.

General psychopathology links burden of recent life events and psychotic symptoms in a network approach

Recent life events have been implicated in the onset and progression of psychosis. However, psychological processes that account for the association are yet to be fully understood. Using a network approach, we aimed to identify pathways linking recent life events and symptoms observed in psychosis. Based on previous literature, we hypothesized that general symptoms would mediate between recent life events and psychotic symptoms. We analyzed baseline data of patients at clinical high risk for psychosis and with recent-onset psychosis (n = 547) from the Personalised Prognostic Tools for Early Psychosis Management (PRONIA) study. In a network analysis, we modeled links between the burden of recent life events and all individual symptoms of the Positive and Negative Syndrome Scale before and after controlling for childhood trauma. To investigate the longitudinal associations between burden of recent life events and symptoms, we analyzed multiwave panel data from seven timepoints up to month 18. Corroborating our hypothesis, burden of recent life events was connected to positive and negative symptoms through general psychopathology, specifically depression, guilt feelings, anxiety and tension, even after controlling for childhood trauma. Longitudinal modeling indicated that on average, burden of recent life events preceded general psychopathology in the individual. In line with the theory of an affective pathway to psychosis, recent life events may lead to psychotic symptoms via heightened emotional distress. Life events may be one driving force of unspecific, general psychopathology described as characteristic of early phases of the psychosis spectrum, offering promising avenues for interventions.

Modeling Social Sensory Processing During Social Computerized Cognitive Training for Psychosis Spectrum: The Resting-State Approach

Background: Greater impairments in early sensory processing predict response to auditory computerized cognitive training (CCT) in patients with recent-onset psychosis (ROP). Little is known about neuroimaging predictors of response to social CCT, an experimental treatment that was recently shown to induce cognitive improvements in patients with psychosis. Here, we investigated whether ROP patients show interindividual differences in sensory processing change and whether different patterns of SPC are (1) related to the differential response to treatment, as indexed by gains in social cognitive neuropsychological tests and (2) associated with unique resting-state functional connectivity (rsFC). Methods: Twenty-six ROP patients completed 10 h of CCT over the period of 4-6 weeks. Subject-specific improvement in one CCT exercise targeting early sensory processing-a speeded facial Emotion Matching Task (EMT)-was studied as potential proxy for target engagement. Based on the median split of SPC from the EMT, two patient groups were created. Resting-state activity was collected at baseline, and bold time series were extracted from two major default mode network (DMN) hubs: left medial prefrontal cortex (mPFC) and left posterior cingulate cortex (PCC). Seed rsFC analysis was performed using standardized Pearson correlation matrices, generated between the average time course for each seed and each voxel in the brain. Results: Based on SPC, we distinguished improvers-i.e., participants who showed impaired performance at baseline and reached the EMT psychophysical threshold during CCT-from maintainers-i.e., those who showed intact EMT performance at baseline and sustained the EMT psychophysical threshold throughout CCT. Compared to maintainers, improvers showed an increase of rsFC at rest between PCC and left superior and medial frontal regions and the cerebellum. Compared to improvers, maintainers showed increased rsFC at baseline between PCC and superior temporal and insular regions bilaterally. Conclusions: In ROP patients with an increase of connectivity at rest in the default mode network, social CCT is still able to induce sensory processing changes that however do not translate into social cognitive gains. Future studies should investigate if impairments in short-term synaptic plasticity are responsible for this lack of response and can be remediated by pharmacological augmentation during CCT.

Effects and moderators of exercise on sleep in adults with cancer: Individual patient data and aggregated meta-analyses

OBJECTIVES

To evaluate the effects of exercise interventions on sleep disturbances and sleep quality in patients with mixed cancer diagnoses, and identify demographic, clinical, and intervention-related moderators of these effects.

METHODS

Individual patient data (IPD) and aggregated meta-analyses of randomized controlled trials (RCTs). Using data from the Predicting OptimaL cAncer RehabIlitation and Supportive care project, IPD of 2173 adults (mean age = 54.8) with cancer from 17 RCTs were analyzed. A complementary systematic search was conducted (until November 2018) to study the overall effects and test the representativeness of analyzed IPD. Effect sizes of exercise effects on self-reported sleep outcomes were calculated for all included RCTs. Linear mixed-effect models were used to evaluate the effects of exercise on post-intervention outcome values, adjusting for baseline values. Moderator effects were studied by testing interactions for demographic, clinical and intervention-related characteristics.

RESULTS

For all 27 eligible RCTs from the updated search, exercise interventions significantly decreased sleep disturbances in adults with cancer (g = -0.09, 95% CI [-0.16; -0.02]). No significant effect was obtained for sleep quality. RCTs included in IPD analyses constituted a representative sample of the published literature. The intervention effects on sleep disturbances were not significantly moderated by any demographic, clinical, or intervention-related factor, nor by sleep disturbances.

CONCLUSIONS

This meta-analysis provides some evidence that, compared to control conditions, exercise interventions may improve sleep disturbances, but not sleep quality, in cancer patients, although this effect is of a small magnitude. Among the investigated variables, none was found to significantly moderate the effect of exercise interventions on sleep disturbances.

Abstract P6-12-06: Effect and moderators of exercise on fatigue in patients with breast cancer: Meta-analysis of individual patient data

Background - Fatigue is one of the most common and disabling complaints in patients with breast cancer and can effectively be reduced by physical exercise, with small to moderate effect sizes. To identify heterogeneity in responses to exercise and to further personalize exercise prescriptions, moderators of exercise effects on fatigue should be investigated. However, most randomized controlled trials (RCTs) are not adequately powered for such analyses. Therefore we conducted meta-analyses using the individual patient data of several exercise RCTs. The aim is to investigate the effect and moderators of physical exercise on cancer-related fatigue in patients with breast cancer.

Methods - Within the Predicting OptimaL cAncer RehabIlitation and Supportive care (POLARIS) consortium, principal investigators of 34 exercise RCTs worldwide have shared their individual patient data. Twenty-two of these RCTs included patients with breast cancer with a total sample size of 3,061. Different questionnaires to assess level of fatigue were used, which was acknowledged by using z-scores in the analysis. A one-step individual patient data meta-analysis, using a linear mixed-effect model adjusted for baseline fatigue, with a random intercept on study (to account for study clustering) was undertaken to investigate effect of exercise on fatigue. The result, a between-group difference in z-scores, corresponds to a Cohen's d effect size. An interaction term was included in the model to assess potential moderators including demographic (age, marital status, education), clinical (body mass index, presence of distant metastasis), intervention-related (intervention timing, delivery mode and duration), and exercise-related (exercise type, frequency, intensity, duration) characteristics.

Results – Exercise significantly reduced fatigue reported by women with breast cancer (β= -0.15, 95% CI -0.21;-0.09). This effect did not differ significantly between patients with different demographic and clinical characteristics (p-valuesinteraction &gt;0.05). Also, neither timing (during or post-treatment) and duration of the intervention, nor exercise-related factors moderated intervention effects on fatigue. Supervised exercise had significantly larger effects on fatigue than unsupervised exercise (βdifference= -0.17, 95%CI -0.28;-0.05). Compared to the control group, supervised exercise significantly improved fatigue (β = -0.21, 95%CI = -0.28;-0.14), while unsupervised exercise did not (β = -0.04, 95%CI = -0.14;0.06).

Conclusion – Exercise significantly reduces fatigue in patients with breast cancer across subgroups formed on the basis of age, marital status, education level, body mass index, and presence of distant metastasis. The effect of exercise is significantly larger when performed under supervision. Hence, exercise, and preferably supervised exercise, represents a viable intervention for the prevention and treatment of fatigue among patients with breast cancer.

Citation Format: van Vulpen JK, Sweegers MG, Kalter J, Peeters PH, Courneya KS, Newton RU, Aaronson NK, Jacobsen PB, Steindorf K, Stuiver MM, Hayes S, Mesters I, Knoop H, Goedendorp M, Mutrie N, Thorsen L, Schmidt M, Sonke GS, Bohus M, James EL, Oldenburg HS, Velthuis MJ, Nollet F, Wenzel J, Wiskemann J, Galvão DA, Chinapaw MJ, Irwin ML, Griffith KA, van Weert E, Daley AJ, McConnachie A, Schulz K-H, Short CE, Plotnikoff RC, Potthoff K, van Beurden M, van Harten WH, Schmitz KH, Winters-Stone KM, Taaffe DR, van Mechelen W, Kersten M-J, Verdonck-de Leeuw IM, Brug J, Buffart LM, May AM. Effect and moderators of exercise on fatigue in patients with breast cancer: Meta-analysis of individual patient data [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P6-12-06.

Lipocalin-2 is expressed by activated granulocytes and keratinocytes in affected skin and reflects disease activity in acne inversa/hidradenitis suppurativa

BACKGROUND

Acne inversa (AI)/hidradenitis suppurativa is a chronic inflammatory disease characterized by painful axillary, inguinal and perianal skin lesions with deep-seated nodules, abscesses and fistulae.

OBJECTIVES

This study aimed to identify and characterize the key players in AI pathogenesis.

METHODS

Epidemiological and anamnestic data for patients with AI were collected, and blood and skin samples were also taken. Healthy participants and patients with psoriasis served as controls. Assessment of samples and cultures of primary cells was performed by enzyme-linked immunosorbent assay, quantitative polymerase chain reaction on reverse transcribed mRNA, and immunohistochemistry.

RESULTS

Of 35 mediators quantified in the blood of patients with AI, lipocalin-2 (LCN2) appeared as one of the most significantly upregulated parameters compared with healthy participants [85·8 ± 12·2 (n = 18) vs. 41·8 ± 4·2 (n = 15); P < 0·001]. Strongly elevated LCN2 expression was present in AI lesions, with granulocytes and keratinocytes being sources of this expression. In vitro, these cells upregulated LCN2 production in response to tumour necrosis factor (TNF)-α, and a positive relationship between systemic TNF-α and LCN2 levels (r_s = 0·55, P = 0·011; n = 20) was evident for AI. LCN2 blood levels correlated with AI disease severity (r_s = 0·65, P < 0·001; n = 29), but not with disease duration, age, sex, body mass index or smoking habit. Detailed analyses revealed a link with the number of skin regions containing nodules and fistulae, but not scars.

CONCLUSIONS

LCN2 might serve as a blood biomarker for the objective assessment of inflammatory activity in AI. We suggest a self-amplification loop comprising TNF-α, neutrophilic granulocytes and LCN2, which contributes to the recurrent skin neutrophil infiltration in AI, clinically evident as pus.

Advances in the treatment of cutaneous lupus erythematosus

Lupus erythematosus (LE) is a multifactorial autoimmune disease with clinical manifestations of differing severity which may present with skin manifestations as primary sign of the disease (cutaneous lupus erythematosus, CLE) or as part of a disease spectrum (systemic lupus erythematosus, SLE). To date, no drugs are approved specifically for the treatment of CLE and only single agents have been applied in randomized controlled trials. Therefore, topical and systemic agents are used "off-label", primarily based on open-label studies, case series, retrospective analyses, and expert opinions. In contrast, several agents, such as hydroxychloroquine, chloroquine, cyclophosphamide, azathioprine, and belimumab, are approved for the treatment of SLE. Recent approaches in the understanding of the molecular pathogenesis of LE enabled the development of further new agents, which target molecules such as interleukin 6 (IL-6) and interferon (IFN). Only single trials, however, applied these new agents in patients with cutaneous involvement of the disease and/or included endpoints which evaluated the efficacy of these agents on skin manifestations. This article provides an updated review on new and recent approaches in the treatment of CLE.

Successful treatment of systemic juvenile xanthogranulomatosis with cytarabine and 2-chlorodeoxyadenosine: case report and review of the literature

The non-Langerhans cell histiocytosis (LCH) juvenile xanthogranulomatosis (JXG) is usually a benign disease limited to the skin. Only a few cases of systemic disease with at least two affected organs and lethal outcomes have been reported to date. Treatment is controversial and no standard protocol is available. We report the rare case of a 22-month-old boy presenting multiple erythematous brownish papules of the head, trunk and legs, which had developed starting from his 6th month of life. Additional symptoms were delayed psychomotor development, hydrocephalus and hepatosplenomegaly. Further diagnostics revealed a systemic JXG with involvement of the skin, central nervous system, liver and spleen. The patient did not respond to initial therapy with prednisone and vinblastine according to protocol III for LCH. However, further therapy with cytarabine and 2-chlorodeoxyadenosine followed by a consolidation phase with 2-chlorodeoxyadenosine alone was successful and the patient is in his 4th year of remission. We provide a comprehensive review of the reported cases of systemic JXG to date.

X-Ray absorption spectra of microsolvated metal cations

Core excited states of microsolvated ions undergo substantial delocalisation whose degree strongly depends on the ion's charge.

Among the S100 proteins, S100A12 is the most significant marker for psoriasis disease activity

BACKGROUND

Psoriasis is a chronic skin disease with deregulation of proteins in the immune system. These proteins include members of the heterogeneous S100 family, which have been discussed as potential biomarkers for disease severity.

OBJECTIVE

The aim of this study was to evaluate the impact of S100A7, S100A8, S100A9 and S100A12 as possible markers for disease activity in patients with psoriasis skin disease.

PATIENTS AND METHODS

S100A7, S100A8, S100A9 and S100A12 mRNA expression was determined in the skin of patients with psoriasis and controls (N = 341) by gene expression analyses. In addition, S100 serum levels were investigated by ELISA in an independent cohort of psoriasis patients (i) untreated, with different manifestations (skin/joints), (ii) under treatment (etanercept) and (iii) healthy controls, (N = 55).

RESULTS

All S100-subtypes included are significantly upregulated in psoriasis skin lesions when compared with atopic dermatitis, lichen ruber and healthy donors. In untreated psoriasis patients, S100A12-serum levels showed the closest association with disease activity (PASI) (r = 0.542; P < 0.01). Serum levels decreased under treatment with etanercept (P < 0.05).

CONCLUSION

Among the investigated S100-proteins, S100A12 showed the closest association with disease activity and therapeutic response and might therefore provide a valuable biomarker for psoriasis.

A novel KRT86 mutation in a Turkish family with monilethrix, and identification of maternal mosaicism

BACKGROUND

Monilethrix is a rare monogenic dystrophic hair loss disorder with high levels of intrafamilial and interfamilial variability. It is characterized by diffuse occipital or temporal alopecia, hair fragility and follicular hyperkeratosis of the occipital region. Mutations in the keratin genes KRT81, KRT83 and KRT86 lead to autosomal dominant monilethrix, whereas mutations in the desmoglein 4 gene (DSG4) cause an autosomal recessive form.

AIM

To identify the mutation in a consanguineous Turkish family with three affected children and apparently unaffected parents.

METHODS

Sequencing analysis of the genes DSG4 and KRT86 was performed. SNaPshot analysis was conducted to quantify the proportion of cells carrying the KRT86 mutation and to confirm maternal mosaicism of KRT86.

RESULTS

No pathogenic mutation was found by sequencing analysis of DSG4; however, analysis of KRT86 revealed a novel mutation, c.1231G>T;p.Glu411*, in exon 7 in the three affected children and their mother. The mutation signal was weaker in the mother than in the three siblings, and SNaPshot analysis revealed substantial mutation-level variation between the children and their mother.

CONCLUSIONS

Our results extend the spectrum of KRT86 mutations and indicate KRT86 mosaicism in the family examined. This study is the first, to our knowledge, to describe mosaicism for a monogenic hair loss disorder, and suggests that mosaicism leads to a mild manifestation of monilethrix.

Foodborne hepatitis A outbreak associated with bakery products in northern Germany, 2012

Binary file ES_Abstracts_Final_ECDC.txt matches

Interferon-α stimulates TRAIL expression in human keratinocytes and peripheral blood mononuclear cells: implications for the pathogenesis of cutaneous lupus erythematosus

BACKGROUND

The tumour necrosis factor-related apoptosis-inducing ligand TRAIL has been shown to participate in the pathogenesis of systemic lupus erythematosus (SLE). The accumulation of apoptotic cell debris has been hypothesized to induce this autoimmune inflammation, and TRAIL may trigger this programmed cell death. Furthermore, TRAIL is among the interferon (IFN)-regulated genes which are typically expressed in the peripheral blood of patients with acute SLE.

OBJECTIVES

As an inappropriate activation of the type I IFN system plays an important role in both SLE and cutaneous lupus erythematosus (CLE) subsets, we hypothesized that TRAIL might also participate in the pathogenesis of CLE.

METHODS

Immunohistochemistry and immunofluorescence analyses were used to identify and localize TRAIL-expressing cells in CLE skin specimens. TRAIL expression in peripheral blood mononuclear cells (PBMC) isolated from patients with CLE was measured by flow cytometry. The impact of IFN-α treatment on TRAIL expression by keratinocytes and PBMC was evaluated by reverse transcription-polymerase chain reaction and flow cytometry.

RESULTS

Keratinocytes are beside CD11c+ and BDCA2+ dendritic cells the major TRAIL-expressing cells in CLE lesions. TRAIL is upregulated on the surface of circulating CD11c+ PBMC isolated from patients with CLE. Treatment of keratinocytes and PBMC with recombinant IFN-α strongly enhances TRAIL expression by these cells. The proapoptotic TRAIL receptor R1 is expressed by keratinocytes in CLE skin lesions.

CONCLUSIONS

TRAIL is strongly expressed in the skin and the blood of patients with CLE and may trigger the apoptotic death of kerationcytes in CLE via the TRAIL receptor R1. An IFN-α-induced TRAIL expression may in this way participate in the pathogenesis of CLE.