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Social dysfunction represents one of the most common signs of neuropsychiatric disorders, such as Schizophrenia (SZ) and Alzheimer's disease (AD). Perturbed socioaffective neural processing is crucially implicated in SZ/AD and generally linked to social dysfunction. Yet, transdiagnostic properties of social dysfunction and its neurobiological underpinnings remain unknown. As part of the European PRISM project, we examined whether social dysfunction maps onto shifts within socioaffective brain systems across SZ and AD patients. We probed coupling of social dysfunction with socioaffective neural processing, as indexed by an implicit facial emotional processing fMRI task, across SZ (N = 46), AD (N = 40) and two age-matched healthy control (HC) groups (N = 26 HC-younger and N = 27 HC-older). Behavioural (i.e., social withdrawal, interpersonal dysfunction, diminished prosocial or recreational activity) and subjective (i.e., feelings of loneliness) aspects of social dysfunction were assessed using the Social Functioning Scale and De Jong-Gierveld loneliness questionnaire, respectively. Across SZ/AD/HC participants, more severe behavioural social dysfunction related to hyperactivity within fronto-parieto-limbic brain systems in response to sad emotions (P = 0.0078), along with hypoactivity of these brain systems in response to happy emotions (P = 0.0418). Such relationships were not found for subjective experiences of social dysfunction. These effects were independent of diagnosis, and not confounded by clinical and sociodemographic factors. In conclusion, behavioural aspects of social dysfunction across SZ/AD/HC participants are associated with shifts within fronto-parieto-limbic brain systems. These findings pinpoint altered socioaffective neural processing as a putative marker for social dysfunction, and could aid personalized care initiatives grounded in social behaviour., Competing Interests: Declaration of competing interest Dr. Arango has been a consultant to or has received honoraria or grants from Acadia, Angelini, Biogen, Boehringer, Gedeon Richter, Janssen Cilag, Lundbeck, Medscape, Menarini, Minerva, Otsuka, Pfizer, Roche, Sage, Servier, Shire, Schering Plough, Sumitomo Dainippon Pharma, Sunovion and Takeda. AM and GRD are full-time employees of P1vital Ltd. GRD is an owner and shareholder of P1vital Ltd. and P1vital Products Ltd. ACB is an employee of P1vital Products Ltd. All other authors declare that they have nothing to disclose., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

Social interactions are essential for well-being. Therefore, researchers increasingly attempt to capture an individual's social context to predict well-being, including mood. Different tools are used to measure various aspects of the social context. Digital phenotyping is a commonly used technology to assess a person's social behavior objectively. The experience sampling method (ESM) can capture the subjective perception of specific interactions. Lastly, egocentric networks are often used to measure specific relationship characteristics. These different methods capture different aspects of the social context over different time scales that are related to well-being, and combining them may be necessary to improve the prediction of well-being. Yet, they have rarely been combined in previous research. To address this gap, our study investigates the predictive accuracy of mood based on the social context. We collected intensive within-person data from multiple passive and self-report sources over a 28-day period in a student sample (Participants: N = 11, ESM measures: N = 1313). We trained individualized random forest machine learning models, using different predictors included in each model summarized over different time scales. Our findings revealed that even when combining social interactions data using different methods, predictive accuracy of mood remained low. The average coefficient of determination over all participants was 0.06 for positive and negative affect and ranged from - 0.08 to 0.3, indicating a large amount of variance across people. Furthermore, the optimal set of predictors varied across participants; however, predicting mood using all predictors generally yielded the best predictions. While combining different predictors improved predictive accuracy of mood for most participants, our study highlights the need for further work using larger and more diverse samples to enhance the clinical utility of these predictive modeling approaches., (© 2024. The Author(s).)

Depression, or major depressive disorder, poses a significant burden for both individuals and society, affecting approximately 10.8% of the general population. This psychiatric disorder leads to approximately 800,000 deaths per year. A combination of genetic and environmental factors such as early life stress (ELS) increase the risk for development of depression in humans, and a clear role for the hippocampus in the pathophysiology of depression has been shown. Nevertheless, the underlying mechanisms of depression remain poorly understood, resulting in a lack of effective treatments. To better understand the core mechanisms underlying the development of depression, we used a cross-species design to investigate shared hippocampal pathophysiological mechanisms in mouse ELS and human depression. Mice were subjected to ELS by a maternal separation paradigm, followed by RNA sequencing analysis of the adult hippocampal tissue. This identified persistent transcriptional changes linked to mitochondrial stress response pathways, with oxidative phosphorylation and protein folding emerging as the main mechanisms affected by maternal separation. Remarkably, there was a significant overlap between the pathways involved in mitochondrial stress response we observed and publicly available RNAseq data from hippocampal tissue of depressive patients. This cross-species conservation of changes in gene expression of mitochondria-related genes suggests that mitochondrial stress may play a pivotal role in the development of depression. Our findings highlight the potential significance of the hippocampal mitochondrial stress response as a core mechanism underlying the development of depression. Further experimental investigations are required to expand our understanding of these mechanisms., Competing Interests: The authors report no conflict of interest., (© 2024 The Authors.)

Approximately 8 % of patients with schizophrenia are diagnosed before age 18, and 18 % experience their first symptoms before age 18. This narrative review explores the management of patients with early-onset schizophrenia (EOS) and childhood-onset schizophrenia (COS) from diagnosis to their transition to adult care settings. Early diagnosis of schizophrenia in children and adolescents is essential for improving outcomes, but delays are common due to overlapping of symptoms with developmental phenomena and other psychiatric conditions, including substance use, and lack of clinicians' awareness. Once diagnosed, antipsychotic treatment is key, with specific second-generation agents generally being preferred due to better tolerability and their broader efficacy evidence-base in youth. Dosing should be carefully individualized, considering age-related differences in drug metabolism and side effect liability. Clinicians must be vigilant in detecting early non-response and consider switching or dose escalation when appropriate. Since early age of illness onset is a consistent risk factor for treatment-resistant schizophrenia (TRS), clinicians need to be competent in diagnosing TRS and using clozapine. Since COS and EOS are associated with cognitive deficits and impaired functioning, psychosocial interventions should be considered to improve overall functioning and quality of life. Good long-term outcomes depend on continuous treatment engagement, and successful transitioning from pediatric to adult care requires careful planning, early preparation, and collaboration between pediatric and adult clinicians. Targeting functional outcomes and quality of life in addition to symptom remission can improve overall patient well-being. Comprehensive evaluations, age-specific assessments, and targeted interventions are needed to address the unique challenges of EOS and COS., Competing Interests: Declaration of competing interest CU Correll has been a consultant and/or advisor to or has received honoraria from: AbbVie, Acadia, Alkermes, Allergan, Angelini, Aristo, Biogen, Boehringer-Ingelheim, Cardio Diagnostics, Cerevel, CNX Therapeutics, Compass Pathways, Darnitsa, Denovo, Gedeon Richter, Hikma, Holmusk, IntraCellular Therapies, Jamjoom Pharma, Janssen/J&J, Karuna, LB Pharma, Lundbeck, MedAvante-ProPhase, MedInCell, Merck, Mindpax, Mitsubishi Tanabe Pharma, Mylan, Neurocrine, Neurelis, Newron, Noven, Novo Nordisk, Otsuka, Pharmabrain, PPD Biotech, Recordati, Relmada, Reviva, Rovi, Sage, Seqirus, SK Life Science, Sunovion, Sun Pharma, Supernus, Takeda, Teva, Tolmar, and Viatris. He provided expert testimony for Janssen and Otsuka. He served on a Data Safety Monitoring Board for Compass Pathways, Denovo, Lundbeck, Relmada, Reviva, Rovi, Supernus, and Teva. He has received grant support from Janssen and Takeda. He received royalties from UpToDate and is also a stock option holder of Cardio Diagnostics, Kuleon Biosciences, LB Pharma, Mindpax, and Quantic. C. Arango has been a consultant to or has received honoraria or grants from Acadia, Angelini, Biogen, Boehringer, Gedeon Richter, Janssen Cilag, Lundbeck, Medscape, Menarini, Minerva, Otsuka, Pfizer, Roche, Sage, Servier, Shire, Schering Plough, Sumitomo Dainippon Pharma, Sunovion and Takeda. B Fagerlund declares travel expenses and writing assistance for the submitted work, funded by Angelini. S Galderisi has received personal fees from Angelini Pharma, Boehringer Ingelheim, Gedeon Richter-Recordati, Janssen, Lundbeck, Otsuka, Recordati Pharmaceuticals, Rovi Pharma, Sunovion Pharmaceuticals, outside the submitted work. MJ Kas has received (non-related) research funding from Novartis. In the last 3 years, he has received fees for lectures from Angelini and Boehringer Ingelheim. S Leucht has been an advisor and/or lecturer and/or has developed educational material for Alkermes, Angelini, Apsen, Eisai, Gedeon Richter, Janssen, Karuna, Kynexis, Lundbeck, Medichem, Medscape, Merck Sharpp and Dome, Mitshubishi, Neurotorium, NovoNordisk, Otsuka, Recordati, Roche, Rovi, Sanofi Aventis, TEVA., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Recently, many funding agencies have released guidelines on the importance of considering sex as a biological variable (SABV) as an experimental factor, aiming to address sex differences and avoid possible sex biases to enhance the reproducibility and translational relevance of preclinical research. In neuroscience and pharmacology, the female sex is often omitted from experimental designs, with researchers generalizing male-driven outcomes to both sexes, risking a biased or limited understanding of disease mechanisms and thus potentially ineffective therapeutics. Herein, we describe key methodological aspects that should be considered when sex is factored into in vitro and in vivo experiments and provide practical knowledge for researchers to incorporate SABV into preclinical research. Both age and sex significantly influence biological and behavioral processes due to critical changes at different timepoints of development for males and females and due to hormonal fluctuations across the rodent lifespan. We show that including both sexes does not require larger sample sizes, and even if sex is included as an independent variable in the study design, a moderate increase in sample size is sufficient. Moreover, the importance of tracking hormone levels in both sexes and the differentiation between sex differences and sex-related strategy in behaviors are explained. Finally, the lack of robust data on how biological sex influences the pharmacokinetic (PK), pharmacodynamic (PD), or toxicological effects of various preclinically administered drugs to animals due to the exclusion of female animals is discussed, and methodological strategies to enhance the rigor and translational relevance of preclinical research are proposed., Competing Interests: Declaration of Competing Interest CD and PP no conflicts. JM no conflicts. IJ no conflicts. MJK no conflicts. MMC no conflicts. HW no conflicts. RS no conflicts. GEH no conflicts. JBB no conflicts. JT no conflicts. CFB no conflicts. AB is an employee and shareholder of PAASP GmbH and a shareholder of PAASP US LLC., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Background: Social interactions are important for well-being, and therefore, researchers are increasingly attempting to capture people's social environment. Many different disciplines have developed tools to measure the social environment, which can be highly variable over time. The experience sampling method (ESM) is often used in psychology to study the dynamics within a person and the social environment. In addition, passive sensing is often used to capture social behavior via sensors from smartphones or other wearable devices. Furthermore, sociologists use egocentric networks to track how social relationships are changing. Each of these methods is likely to tap into different but important parts of people's social environment. Thus far, the development and implementation of these methods have occurred mostly separately from each other., Objective: Our aim was to synthesize the literature on how these methods are currently used to capture the changing social environment in relation to well-being and assess how to best combine these methods to study well-being., Methods: We conducted a scoping review according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines., Results: We included 275 studies. In total, 3 important points follow from our review. First, each method captures a different but important part of the social environment at a different temporal resolution. Second, measures are rarely validated (>70% of ESM studies and 50% of passive sensing studies were not validated), which undermines the robustness of the conclusions drawn. Third, a combination of methods is currently lacking (only 15/275, 5.5% of the studies combined ESM and passive sensing, and no studies combined all 3 methods) but is essential in understanding well-being., Conclusions: We highlight that the practice of using poorly validated measures hampers progress in understanding the relationship between the changing social environment and well-being. We conclude that different methods should be combined more often to reduce the participants' burden and form a holistic perspective on the social environment., (©Anna M Langener, Gert Stulp, Martien J Kas, Laura F Bringmann. Originally published in JMIR Mental Health (https://mental.jmir.org), 17.03.2023.)

The concept of resilience, i.e., the capacity of a system to bounce back after a stressor, is gaining interest across many fields of science, policy, and practice. To date, resilience research in people with cognitive decline has predominantly addressed the early stages of decline. We propose that: (1) resilience is a relevant concept in all stages of cognitive decline; and (2) a socio-ecological, multisystem perspective on resilience is required to advance understanding of, and care and support for people with cognitive decline and their support networks. We substantiate our position with literature and examples. Resilience helps understand differences in response to risk factors of (further) cognitive decline and informs personalised prevention. In a curative context, interventions to strengthen resilience aim to boost recovery from cognitive decline. In care for people with dementia, resilience-focused interventions can strengthen coping mechanisms to maintain functioning and well-being of the individual and their support network. A good example of improving resilience in the social and policy context is the introduction of age-friendly cities and dementia-friendly communities. Good care for people with cognitive decline requires a health and social care system that can adapt to changes in demand. Given the interdependency of resilience at micro-, meso- and macro-levels, an integrative socio-ecological perspective is required. Applying the concept of resilience in the field of cognitive decline opens new horizons for research to improve understanding, predicting, intervening on health and social care needs for the increasing population with cognitive decline., (© 2023 The Author(s). Published by S. Karger AG, Basel.)

The influence of protocol standardization between laboratories on their replicability of preclinical results has not been addressed in a systematic way. While standardization is considered good research practice as a means to control for undesired external noise (i.e., highly variable results), some reports suggest that standardized protocols may lead to idiosyncratic results, thus undermining replicability. Through the EQIPD consortium, a multi-lab collaboration between academic and industry partners, we aimed to elucidate parameters that impact the replicability of preclinical animal studies. To this end, 3 experimental protocols were implemented across 7 laboratories. The replicability of results was determined using the distance travelled in an open field after administration of pharmacological compounds known to modulate locomotor activity (MK-801, diazepam, and clozapine) in C57BL/6 mice as a worked example. The goal was to determine whether harmonization of study protocols across laboratories improves the replicability of the results and whether replicability can be further improved by systematic variation (heterogenization) of 2 environmental factors (time of testing and light intensity during testing) within laboratories. Protocols were tested in 3 consecutive stages and differed in the extent of harmonization across laboratories and standardization within laboratories: stage 1, minimally aligned across sites (local protocol); stage 2, fully aligned across sites (harmonized protocol) with and without systematic variation (standardized and heterogenized cohort); and stage 3, fully aligned across sites (standardized protocol) with a different compound. All protocols resulted in consistent treatment effects across laboratories, which were also replicated within laboratories across the different stages. Harmonization of protocols across laboratories reduced between-lab variability substantially compared to each lab using their local protocol. In contrast, the environmental factors chosen to introduce systematic variation within laboratories did not affect the behavioral outcome. Therefore, heterogenization did not reduce between-lab variability further compared to the harmonization of the standardized protocol. Altogether, these findings demonstrate that subtle variations between lab-specific study protocols may introduce variation across independent replicate studies even after protocol harmonization and that systematic heterogenization of environmental factors may not be sufficient to account for such between-lab variation. Differences in replicability of results within and between laboratories highlight the ubiquity of study-specific variation due to between-lab variability, the importance of transparent and fine-grained reporting of methodologies and research protocols, and the importance of independent study replication., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2022 Arroyo-Araujo et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Social dysfunction is commonly present in neuropsychiatric disorders of schizophrenia (SZ) and Alzheimer's disease (AD). Theory of Mind (ToM) deficits have been linked to social dysfunction in disease-specific studies. Nevertheless, it remains unclear how ToM is related to social functioning across these disorders, and which factors contribute to this relationship. We investigated transdiagnostic associations between ToM and social functioning among SZ/AD patients and healthy controls, and explored to what extent these associations relate to information processing speed or facial emotion recognition capacity. A total of 163 participants were included (SZ: n=56, AD: n=50 and age-matched controls: n=57). Social functioning was assessed with the Social Functioning Scale (SFS) and the De Jong-Gierveld Loneliness Scale (LON). ToM was measured with the Hinting Task. Information processing speed was measured by the Digit Symbol Substitution Test (DSST) and facial emotion recognition capacity by the facial emotion recognition task (FERT). Case-control deficits in Hinting Task performance were larger in AD (r rb  = -0.57) compared to SZ (r rb  = -0.35). Poorer Hinting Task performance was transdiagnostically associated with the SFS (β Hinting-Task  = 1.20, p<0.01) and LON (β Hinting-Task  = -0.27, p<0.05). DSST, but not FERT, reduced the association between the SFS and Hinting Task performance, however the association remained significant (β Hinting-Task  = 0.95, p<0.05). DSST and FERT performances did not change the association between LON and Hinting Task performance. Taken together, ToM deficits are transdiagnostically associated with social dysfunction and this is partly related to reduced information processing speed., Competing Interests: Conflicts of Interest G.R. Dawson is co-owner and employee of P1vital LTD who provide the FERT and the digital version of the DSST for this study. A. Bilderbeck is an employee of P1vital LTD who provide the FERT and the digital version of the DSST for this study. Dr. Arango has been a consultant to or has received honoraria or grants from Acadia, Angelini, Biogen, Boehringer, Gedeon Richter, Janssen Cilag, Lundbeck, Medscape, Minerva, Otsuka, Pfizer, Roche, Sage, Servier, Shire, Schering Plough, Sumitomo Dainippon Pharma, Sunovion and Takeda. Dr van der Wee was on advisory boards for Pfizer, Servier and Eli Lilly and received grants from the EU and the Netherlands Organisation for Health Research and Development. All other authors declare that they have no conflicts of interest., (Copyright © 2022. Published by Elsevier B.V.)

Background: Poor social health has been linked to a risk of neuropsychiatric disorders. Neuroimaging studies have shown associations between social health and global white matter microstructural integrity. We aimed to identify which white matter tracts are involved in these associations., Methods: Social health markers (loneliness, perceived social support, and partnership status) and white matter microstructural integrity of 15 white matter tracts (identified with probabilistic tractography after diffusion magnetic resonance imaging) were collected for 3352 participants (mean age 58.4 years, 54.9% female) from 2002 to 2008 in the Rotterdam Study. Cross-sectional associations were studied using multivariable linear regression., Results: Loneliness was associated with higher mean diffusivity (MD) in the superior thalamic radiation and the parahippocampal part of the cingulum (standardized mean difference for both tracts: 0.21, 95% CI, 0.09 to 0.34). Better perceived social support was associated with lower MD in the forceps minor (standardized mean difference per point increase in social support: -0.06, 95% CI, -0.09 to -0.03), inferior fronto-occipital fasciculus, and uncinate fasciculus. In male participants, better perceived social support was associated with lower MD in the forceps minor, and not having a partner was associated with lower fractional anisotropy in the forceps minor. Loneliness was associated with higher MD in the superior thalamic radiation in female participants only., Conclusions: Social health was associated with tract-specific white matter microstructure. Loneliness was associated with lower integrity of limbic and sensorimotor tracts, whereas better perceived social support was associated with higher integrity of association and commissural tracts, indicating that social health domains involve distinct neural pathways of the brain., (© 2022 The Authors.)

Poor neurocognitive performance has been associated with poor functional outcome in schizophrenia (SCZ) in past studies. Nonetheless, the likely association between neurocognition and social withdrawal has never been investigated. The aim of our study was to investigate in a large and heterogeneous sample of SCZ patient cross-sectional associations between neurocognitive domains and social withdrawal. The sample included 761 SCZ patients who completed the baseline visit in the CATIE study. Neurocognition was assessed by a comprehensive battery of tests resulting in five domain scores and a composite score. Social withdrawal was measured by a specific item of the Heinrichs-Carpenter Quality of Life Scale. Social withdrawal was associated with a lower score in the neurocognitive composite score and in 'Verbal memory,' 'Processing speed' and 'Working memory' scores. 'Verbal memory' score showed the strongest association with social withdrawal. Eight percent of the total variance of social withdrawal was explained by these three cognitive domains and additional clinical and sociodemographic factors (education years, PANSS positive symptoms score, and employment). Our results confirmed the wide heterogeneity and specificity of the correlation between neurocognitive domains and indicators of functional outcome in SCZ, underlining the role of certain neurocognitive abilities in social withdrawal., (Copyright © 2022 The Author(s). Published by Wolters Kluwer Health, Inc.)

Background: Social functioning is often impaired in schizophrenia (SZ) and Alzheimer's disease (AD). However, commonalities and differences in social dysfunction among these patient groups remain elusive., Materials and Methods: Using data from the PRISM study, behavioral (all subscales and total score of the Social Functioning Scale) and affective (perceived social disability and loneliness) indicators of social functioning were measured in patients with SZ (N = 56), probable AD (N = 50) and age-matched healthy controls groups (HC, N = 29 and N = 28). We examined to what extent social functioning differed between disease and age-matched HC groups, as well as between patient groups. Furthermore, we examined how severity of disease and mood were correlated with social functioning, irrespective of diagnosis., Results: As compared to HC, both behavioral and affective social functioning seemed impaired in SZ patients (Cohen's d's 0.81-1.69), whereas AD patients mainly showed impaired behavioral social function (Cohen's d's 0.65-1.14). While behavioral indices of social functioning were similar across patient groups, SZ patients reported more perceived social disability than AD patients (Cohen's d's 0.65). Across patient groups, positive mood, lower depression and anxiety levels were strong determinants of better social functioning (p's <0.001), even more so than severity of disease., Conclusions: AD and SZ patients both exhibit poor social functioning in comparison to age- and sex matched HC participants. Social dysfunction in SZ patients may be more severe than in AD patients, though this may be due to underreporting by AD patients. Across patients, social functioning appeared as more influenced by mood states than by severity of disease., Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: CA has been a consultant to or has received honoraria or grants from Acadia, Angelini, Gedeon Richter, Janssen Cilag, Lundbeck, Minerva, Otsuka, Roche, Sage, Servier, Shire, Schering Plough, Sumitomo Dainippon Pharma, Sunovion and Takeda. ACB has received salaries from P1vital Ltd. MK has received (non-related) research funding from Novartis. BP has received (non-related) research funding from Jansen Research and Boehringer Ingelheim. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

Background: Emotion recognition constitutes a pivotal process of social cognition. It involves decoding social cues (e.g., facial expressions) to maximise social adjustment. Current theoretical models posit the relationship between social withdrawal factors (social disengagement, lack of social interactions and loneliness) and emotion decoding., Objective: To investigate the role of social withdrawal in patients with schizophrenia (SZ) or probable Alzheimer's disease (AD), neuropsychiatric conditions associated with social dysfunction., Methods: A sample of 156 participants was recruited: schizophrenia patients (SZ; n = 53), Alzheimer's disease patients (AD; n = 46), and two age-matched control groups (SZc, n = 29; ADc, n = 28). All participants provided self-report measures of loneliness and social functioning, and completed a facial emotion detection task., Results: Neuropsychiatric patients (both groups) showed poorer performance in detecting both positive and negative emotions compared with their healthy counterparts (p < .01). Social withdrawal was associated with higher accuracy in negative emotion detection, across all groups. Additionally, neuropsychiatric patients with higher social withdrawal showed lower positive emotion misclassification., Conclusions: Our findings help to detail the similarities and differences in social function and facial emotion recognition in two disorders rarely studied in parallel, AD and SZ. Transdiagnostic patterns in these results suggest that social withdrawal is associated with heightened sensitivity to negative emotion expressions, potentially reflecting hypervigilance to social threat. Across the neuropsychiatric groups specifically, this hypervigilance associated with social withdrawal extended to positive emotion expressions, an emotional-cognitive bias that may impact social functioning in people with severe mental illness., (Copyright © 2021. Published by Elsevier Inc.)

Social withdrawal is an early manifestation of several neuropsychiatric disorders, and it is characterised by a gradual disengagement from social interactions, potentially leading to complete isolation. This study investigated the association between social withdrawal at baseline and short-term symptom remission in five independent cohorts, including patients with major depressive disorder (MDD), bipolar spectrum disorders, and schizophrenia. Measures of social withdrawal were derived in each study, and clinical remission was estimated based on the psychopathological severity assessed after short-term psychopharmacological treatment (12 weeks). Logistic regression was performed in each sample, adjusting for age and baseline psychopathological severity residualised for social withdrawal. Results were then meta-analysed across samples within a random-effect framework. A total of 4461 patients were included in the analyses (3195 patients with MDD, 655 with bipolar spectrum disorders and 611 with schizophrenia). The meta-analysis showed that higher baseline levels of social withdrawal were associated with a decreased likelihood of short-term remission (ORadj = 0.67, 95% CI, 0.58-0.79, P = 5.28 × 10-7), with the strongest effect in patients with schizophrenia. Overall, our study highlighted the need to address social withdrawal in the early phases of the disease to promote symptom remission in patients with major psychiatric disorders. Understanding the neurobiology underlying social withdrawal may aid the development of medications that can specifically reverse social impairment, thereby fostering clinical remission., (Copyright © 2022 The Author(s). Published by Wolters Kluwer Health, Inc.)

Objectives: Social dysfunction is one of the most common signs of major neuropsychiatric disorders. The Default Mode Network (DMN) is crucially implicated in both psychopathology and social dysfunction, although the transdiagnostic properties of social dysfunction remains unknown. As part of the pan-European PRISM (Psychiatric Ratings using Intermediate Stratified Markers) project, we explored cross-disorder impact of social dysfunction on DMN connectivity., Methods: We studied DMN intrinsic functional connectivity in relation to social dysfunction by applying Independent Component Analysis and Dual Regression on resting-state fMRI data, among schizophrenia (SZ; N   =   48), Alzheimer disease (AD; N   =   47) patients and healthy controls (HC; N   =   55). Social dysfunction was operationalised via the Social Functioning Scale (SFS) and De Jong-Gierveld Loneliness Scale (LON)., Results: Both SFS and LON were independently associated with diminished DMN connectional integrity within rostromedial prefrontal DMN subterritories ( p corrected range   =   0.02-0.04). The combined effect of these indicators (Mean.SFS + LON) on diminished DMN connectivity was even more pronounced (both spatially and statistically), independent of diagnostic status, and not confounded by key clinical or sociodemographic effects, comprising large sections of rostromedial and dorsomedial prefrontal cortex ( p corrected =0.01)., Conclusions: These findings pinpoint DMN connectional alterations as putative transdiagnostic endophenotypes for social dysfunction and could aid personalised care initiatives grounded in social behaviour.

Sleep deprivation has a negative impact on hippocampus-dependent memory, which is thought to depend on cellular plasticity. We previously found that 5 h of sleep deprivation robustly decreases dendritic spine density in the CA1 area of the hippocampus in adult male mice. However, recent work by others suggests that sleep deprivation increases the density of certain spine types on specific dendritic branches. Based on these recent findings and our previous work, we conducted a more in-depth analysis of different spine types on branches 1, 2 and 5 of both apical and basal dendrites to assess whether 5 h of sleep deprivation may have previously unrecognized spine-type and branch-specific effects. This analysis shows no spine-type specific changes on branch 1 and 2 of apical dendrites after sleep deprivation. In contrast, sleep deprivation decreases the number of mushroom and branched spines on branch 5. Likewise, sleep deprivation reduces thin, mushroom and filopodia spine density on branch 5 of the basal dendrites, without affecting spines on branch 1 and 2. Our findings indicate that sleep deprivation leads to local branch-specific reduction in the density of individual spine types, and that local effects might not reflect the overall impact of sleep deprivation on CA1 structural plasticity. Moreover, our analysis underscores that focusing on a subset of dendritic branches may lead to potential misinterpretation of the overall impact of, in this case, sleep deprivation on structural plasticity., (© 2021 The Authors. Journal of Sleep Research published by John Wiley & Sons Ltd on behalf of European Sleep Research Society.)

Background: Questionnaires are the current hallmark for quantifying social functioning in human clinical research. In this study, we compared self- and proxy-rated (caregiver and researcher) assessments of social functioning in Schizophrenia (SZ) and Alzheimer's disease (AD) patients and evaluated if the discrepancy between the two assessments is mediated by disease-related factors such as symptom severity., Methods: We selected five items from the WHO Disability Assessment Schedule 2.0 (WHODAS) to assess social functioning in 53 AD and 61 SZ patients. Caregiver- and researcher-rated assessments of social functioning were used to calculate the discrepancies between self-rated and proxy-rated assessments. Furthermore, we used the number of communication events via smartphones to compare the questionnaire outcomes with an objective measure of social behaviour., Results: WHODAS results revealed that both AD (p < 0.001) and SZ (p < 0.004) patients significantly overestimate their social functioning relative to the assessment of their caregivers and/or researchers. This overestimation is mediated by the severity of cognitive impairments (MMSE; p = 0.019) in AD, and negative symptoms (PANSS; p = 0.028) in SZ. Subsequently, we showed that the proxy scores correlated more strongly with the smartphone communication events of the patient when compared to the patient-rated questionnaire scores (self; p = 0.076, caregiver; p < 0.001, researcher-rated; p = 0.046)., Conclusion: Here we show that the observed overestimation of WHODAS social functioning scores in AD and SZ patients is partly driven by disease-related biases such as cognitive impairments and negative symptoms, respectively. Therefore, we postulate the development and implementation of objective measures of social functioning that may be less susceptible to such biases., (Copyright © 2020 The Authors. Published by Elsevier Ltd.. All rights reserved.)

The mouse is widely used as an experimental model to study visual processing. To probe how the visual system detects changes in the environment, functional paradigms in freely behaving mice are strongly needed. We developed and validated the first EEG-based method to investigate visual deviance detection in freely behaving mice. Mice with EEG implants were exposed to a visual deviant detection paradigm that involved changes in light intensity as standard and deviant stimuli. By subtracting the standard from the deviant evoked waveform, deviant detection was evident as bi-phasic negativity (starting around 70 ms) in the difference waveform. Additionally, deviance-associated evoked (beta/gamma) and induced (gamma) oscillatory responses were found. We showed that the results were stimulus-independent by applying a "flip-flop" design and the results showed good repeatability in an independent measurement. Together, we put forward a validated, easy-to-use paradigm to measure visual deviance processing in freely behaving mice., Competing Interests: Declaration of Competing Interest None, (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

Laboratory workflows and preclinical models have become increasingly diverse and complex. Confronted with the dilemma of a multitude of information with ambiguous relevance for their specific experiments, scientists run the risk of overlooking critical factors that can influence the planning, conduct and results of studies and that should have been considered a priori . To address this problem, we developed "PEERS" (Platform for the Exchange of Experimental Research Standards), an open-access online platform that is built to aid scientists in determining which experimental factors and variables are most likely to affect the outcome of a specific test, model or assay and therefore ought to be considered during the design, execution and reporting stages. The PEERS database is categorized into in vivo and in vitro experiments and provides lists of factors derived from scientific literature that have been deemed critical for experimentation. The platform is based on a structured and transparent system for rating the strength of evidence related to each identified factor and its relevance for a specific method/model. In this context, the rating procedure will not solely be limited to the PEERS working group but will also allow for a community-based grading of evidence. We here describe a working prototype using the Open Field paradigm in rodents and present the selection of factors specific to each experimental setup and the rating system. PEERS not only offers users the possibility to search for information to facilitate experimental rigor, but also draws on the engagement of the scientific community to actively expand the information contained within the platform. Collectively, by helping scientists search for specific factors relevant to their experiments, and to share experimental knowledge in a standardized manner, PEERS will serve as a collaborative exchange and analysis tool to enhance data validity and robustness as well as the reproducibility of preclinical research. PEERS offers a vetted, independent tool by which to judge the quality of information available on a certain test or model, identifies knowledge gaps and provides guidance on the key methodological considerations that should be prioritized to ensure that preclinical research is conducted to the highest standards and best practice., Competing Interests: AB and CE are employees and shareholders of PAASP GmbH and PAASP US LLC. AB was an employee and shareholder of Exciva GmbH and Synventa LLC. CF-B was employed by Cohen Veterans Bioscience, which has funded the initial stages of the PEERS project development. MP was an employee of EpiEndo Pharmaceutical EHF and previously of Fraunhofer IME-TMP and GSK. TS was an employee of Janssen Pharmaceutica. AH was employed by Y47 Consultancy. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Sil, Bespalov, Dalla, Ferland-Beckham, Herremans, Karantzalos, Kas, Kokras, Parnham, Pavlidi, Pristouris, Steckler, Riedel and Emmerich.)

Circadian clock genes serve as the molecular basis for animals' ~24-h internal timekeeping. Clock gene expression inside and outside of the mammalian brain's circadian pacemaker (i.e. the SCN) integrates temporal information into a wealth of physiological processes. Ample data suggests that in addition to canonical cellular timekeeping functions, clock proteins also interact with proteins involved in cellular processes not related to timekeeping, including protein regulation and the interaction with other signaling mechanisms not directly linked to the regulation of circadian rhythms. Indeed, recent data suggests that clock genes outside the SCN are involved in fundamental brain processes such as sleep/wakefulness, stress and memory. The role of clock genes in these brain processes are complex and divers, influencing many molecular pathways and phenotypes. In this review, we will discuss recent work on the involvement of clock genes in sleep, stress, and memory. Moreover, we raise the controversial possibility that these functions may be under certain circumstances independent of their circadian timekeeping function., (Copyright © 2021 The Author(s). Published by Elsevier Inc. All rights reserved.)

Policymakers aim to move toward animal-free alternatives for scientific research and have introduced very strict regulations for animal research. We argue that, for neuroscience research, until viable and translational alternatives become available and the value of these alternatives has been proven, the use of animals should not be compromised., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Levels of sociability are continuously distributed in the general population, and decreased sociability represents an early manifestation of several brain disorders. Here, we investigated the genetic underpinnings of sociability in the population. We performed a genome-wide association study (GWAS) of a sociability score based on four social functioning-related self-report questions from 342,461 adults in the UK Biobank. Subsequently we performed gene-wide and functional follow-up analyses. Robustness analyses were performed in the form of GWAS split-half validation analyses, as well as analyses excluding neuropsychiatric cases. Using genetic correlation analyses as well as polygenic risk score analyses we investigated genetic links of our sociability score to brain disorders and social behavior outcomes. Individuals with autism spectrum disorders, bipolar disorder, depression, and schizophrenia had a lower sociability score. The score was significantly heritable (SNP h 2 of 6%). We identified 18 independent loci and 56 gene-wide significant genes, including genes like ARNTL, DRD2, and ELAVL2. Many associated variants are thought to have deleterious effects on gene products and our results were robust. The sociability score showed negative genetic correlations with autism spectrum, disorders, depression, schizophrenia, and two sociability-related traits-loneliness and social anxiety-but not with bipolar disorder or Alzheimer's disease. Polygenic risk scores of our sociability GWAS were associated with social behavior outcomes within individuals with bipolar disorder and with major depressive disorder. Variation in population sociability scores has a genetic component, which is relevant to several psychiatric disorders. Our findings provide clues towards biological pathways underlying sociability., (© 2021. The Author(s).)

While high risk of failure is an inherent part of developing innovative therapies, it can be reduced by adherence to evidence-based rigorous research practices. Supported through the European Union's Innovative Medicines Initiative, the EQIPD consortium has developed a novel preclinical research quality system that can be applied in both public and private sectors and is free for anyone to use. The EQIPD Quality System was designed to be suited to boost innovation by ensuring the generation of robust and reliable preclinical data while being lean, effective and not becoming a burden that could negatively impact the freedom to explore scientific questions. EQIPD defines research quality as the extent to which research data are fit for their intended use. Fitness, in this context, is defined by the stakeholders, who are the scientists directly involved in the research, but also their funders, sponsors, publishers, research tool manufacturers, and collaboration partners such as peers in a multi-site research project. The essence of the EQIPD Quality System is the set of 18 core requirements that can be addressed flexibly, according to user-specific needs and following a user-defined trajectory. The EQIPD Quality System proposes guidance on expectations for quality-related measures, defines criteria for adequate processes (i.e. performance standards) and provides examples of how such measures can be developed and implemented. However, it does not prescribe any pre-determined solutions. EQIPD has also developed tools (for optional use) to support users in implementing the system and assessment services for those research units that successfully implement the quality system and seek formal accreditation. Building upon the feedback from users and continuous improvement, a sustainable EQIPD Quality System will ultimately serve the entire community of scientists conducting non-regulated preclinical research, by helping them generate reliable data that are fit for their intended use., Competing Interests: AB AB is an employee and/or shareholder at PAASP GmbH, PAASP US LLC, Exciva GmbH, Synventa LLC, Ritec Pharma, RB, MA, LB, Nd, EC, AD, RF, VG, SH, MH, MK, MP, PP, EP, LR, GR, MR, JS, MS, CS, VV, JV, KW No competing interests declared, AG AG are employees of Janssen / Johnson & Johnson and shareholders at Johnson & Johnson, BG, CE BG and CE are employees and shareholders at PAASP GmbH. JG JG is an employee of AAALAC International that is an EQIPD Associated Collaborator. VC, CF VC and CFC are employees of Porsolt. IL, FD IAL and FD are employees of Sanofi. LM LM is an employee and shareholder of UCB. SB SB is an employee of Novartis Pharma. BA BA is an employee and shareholder of Pfizer. The views and opinions expressed in this article are those of the individual author and should not be attributed to Pfizer, its directors, officers, employees, affiliates, or any organization with which the author is employed or affiliated. CF AB, BA, NdB, UD, CFB, PK, MK, MM, PM, PP, GR, JS, and TS are members of the Preclinical Data Forum (co-chairs - AB and TS), a network financially and organizationally supported by ECNP and Cohen Veterans Bioscience. PK PK is an employee and shareholder at PAASP US LLC. CK UD and CK receive funding from Volkswagen Foundation, PM PM is owner of Cerbascience Consulting, HP HP has received during the last three years consulting and speaking fees and/or funding for collaborative projects from Bayer, Roche, Zogenix, and Eisai. KW KW is a consultant of Avertim, Brussels, Belgium, support for this contribution was funded by Janssen Pharmaceutica NV. MM MM, UD and TS are members of the Advisory Board at PAASP. MM, UD and TS are members of the ARRIVE guidelines working group. UD UD and CK receive funding from Volkswagen Foundation. MM, UD and TS are members of the Advisory Board at PAASP. MM, UD and TS are members of the ARRIVE guidelines working group. TS MM, UD and TS are members of the Advisory Board at PAASP. MM, UD and TS are members of the ARRIVE guidelines working group. TS is an AAALAC ad-hoc specialist. TS and AG are employees of Janssen / Johnson & Johnson and shareholders at Johnson & Johnson., (© 2021, Bespalov et al.)

Background: Digital technologies have the potential to provide objective and precise tools to detect depression-related symptoms. Deployment of digital technologies in clinical research can enable collection of large volumes of clinically relevant data that may not be captured using conventional psychometric questionnaires and patient-reported outcomes. Rigorous methodology studies to develop novel digital endpoints in depression are warranted. Objective: We conducted an exploratory, cross-sectional study to evaluate several digital technologies in subjects with major depressive disorder (MDD) and persistent depressive disorder (PDD), and healthy controls. The study aimed at assessing utility and accuracy of the digital technologies as potential diagnostic tools for unipolar depression, as well as correlating digital biomarkers to clinically validated psychometric questionnaires in depression. Methods: A cross-sectional, non-interventional study of 20 participants with unipolar depression (MDD and PDD/dysthymia) and 20 healthy controls was conducted at the Centre for Human Drug Research (CHDR), the Netherlands. Eligible participants attended three in-clinic visits (days 1, 7, and 14), at which they underwent a series of assessments, including conventional clinical psychometric questionnaires and digital technologies. Between the visits, there was at-home collection of data through mobile applications. In all, seven digital technologies were evaluated in this study. Three technologies were administered via mobile applications: an interactive tool for the self-assessment of mood, and a cognitive test; a passive behavioral monitor to assess social interactions and global mobility; and a platform to perform voice recordings and obtain vocal biomarkers. Four technologies were evaluated in the clinic: a neuropsychological test battery; an eye motor tracking system; a standard high-density electroencephalogram (EEG)-based technology to analyze the brain network activity during cognitive testing; and a task quantifying bias in emotion perception. Results: Our data analysis was organized by technology - to better understand individual features of various technologies. In many cases, we obtained simple, parsimonious models that have reasonably high diagnostic accuracy and potential to predict standard clinical outcome in depression. Conclusion: This study generated many useful insights for future methodology studies of digital technologies and proof-of-concept clinical trials in depression and possibly other indications., Competing Interests: OS, JC, KH, LG, VD, FA, JP, VV, AD, BG-M, KB, MD, and J-HC were employed by Novartis. FC was employed by Cambridge Cognition. JA was employed by Neurotrack Technologies, Inc. ZP, GI, and OL were employed by ElMindA, Ltd. DJ was employed by Sonde Health, Inc. AZ, RZ, KR, ZZ, and GJ were employed by CHDR. The remaining author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Sverdlov, Curcic, Hannesdottir, Gou, De Luca, Ambrosetti, Zhang, Praestgaard, Vallejo, Dolman, Gomez-Mancilla, Biliouris, Deurinck, Cormack, Anderson, Bott, Peremen, Issachar, Laufer, Joachim, Jagesar, Jongs, Kas, Zhuparris, Zuiker, Recourt, Zuilhof, Cha and Jacobs.)

The lack of translation from basic research into new medicines is a major challenge in CNS drug development. The need to use novel approaches relying on (i) patient clustering based on neurobiology irrespective to symptomatology and (ii) quantitative biomarkers focusing on evolutionarily preserved neurobiological systems allowing back-translation from clinical to nonclinical research has been highlighted. Here we sought to evaluate the mismatch negativity (MMN) response in schizophrenic (SZ) patients, Alzheimer's disease (AD) patients, and age-matched healthy controls. To evaluate back-translation of the MMN response, we developed EEG-based procedures allowing the measurement of MMN-like responses in a rat model of schizophrenia and a mouse model of AD. Our results indicate a significant MMN attenuation in SZ but not in AD patients. Consistently with the clinical findings, we observed a significant attenuation of deviance detection (~104.7%) in rats subchronically exposed to phencyclidine, while no change was observed in APP/PS1 transgenic mice when compared to wild type. This study provides new insight into the cross-disease evaluation of the MMN response. Our findings suggest further investigations to support the identification of neurobehavioral subtypes that may help patients clustering for precision medicine intervention. Furthermore, we provide evidence that MMN could be used as a quantitative/objective efficacy biomarker during both preclinical and clinical stages of SZ drug development.

Background: Digital phenotyping, the measurement of human behavioral phenotypes using personal devices, is rapidly gaining popularity. Novel initiatives, ranging from software prototypes to user-ready research platforms, are innovating the field of biomedical research and health care apps. One example is the BEHAPP project, which offers a fully managed digital phenotyping platform as a service. The innovative potential of digital phenotyping strategies resides among others in their capacity to objectively capture measurable and quantitative components of human behavior, such as diurnal rhythm, movement patterns, and communication, in a real-world setting. The rapid development of this field underscores the importance of reliability and safety of the platforms on which these novel tools are operated. Large-scale studies and regulated research spaces (eg, the pharmaceutical industry) have strict requirements for the software-based solutions they use. Security and sustainability are key to ensuring continuity and trust. However, the majority of behavioral monitoring initiatives have not originated primarily in these regulated research spaces, which may be why these components have been somewhat overlooked, impeding the further development and implementation of such platforms in a secure and sustainable way., Objective: This study aims to provide a primer on the requirements and operational guidelines for the development and operation of a secure behavioral monitoring platform., Methods: We draw from disciplines such as privacy law, information, and computer science to identify a set of requirements and operational guidelines focused on security and sustainability. Taken together, the requirements and guidelines form the foundation of the design and implementation of the BEHAPP behavioral monitoring platform., Results: We present the base BEHAPP data collection and analysis flow and explain how the various concepts from security and sustainability are addressed in the design., Conclusions: Digital phenotyping initiatives are steadily maturing. This study helps the field and surrounding stakeholders to reflect upon and progress toward secure and sustainable operation of digital phenotyping-driven research., (©Raj R Jagesar, Jacob A Vorstman, Martien J Kas. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 07.04.2021.)

Neurodevelopmental and neuropsychiatric disorders, such as autism spectrum disorders (ASD), anorexia nervosa (AN), Alzheimer's disease (AD), and schizophrenia (SZ), are heterogeneous brain disorders with unknown etiology. Genome wide studies have revealed a wide variety of risk genes for these disorders, indicating a biological link between genetic signaling pathways and brain pathology. A unique risk gene is Contactin 4 (Cntn4), an Ig cell adhesion molecule (IgCAM) gene, which has been associated with several neuropsychiatric disorders including ASD, AN, AD, and SZ. Here, we investigated the Cntn4 gene knockout (KO) mouse model to determine whether memory dysfunction and altered brain plasticity, common neuropsychiatric symptoms, are affected by Cntn4 genetic disruption. For that purpose, we tested if Cntn4 genetic disruption affects CA1 synaptic transmission and the ability to induce LTP in hippocampal slices. Stimulation in CA1 striatum radiatum significantly decreased synaptic potentiation in slices of Cntn4 KO mice. Neuroanatomical analyses showed abnormal dendritic arborization and spines of hippocampal CA1 neurons. Short- and long-term recognition memory, spatial memory, and fear conditioning responses were also assessed. These behavioral studies showed increased contextual fear conditioning in heterozygous and homozygous KO mice, quantified by a gene-dose dependent increase in freezing response. In comparison to wild-type mice, Cntn4-deficient animals froze significantly longer and groomed more, indicative of increased stress responsiveness under these test conditions. Our electrophysiological, neuro-anatomical, and behavioral results in Cntn4 KO mice suggest that Cntn4 has important functions related to fear memory possibly in association with the neuronal morphological and synaptic plasticity changes in hippocampus CA1 neurons.

The COVID-19 pandemic has led to unprecedented societal changes limiting us in our mobility and our ability to connect with others in person. These unusual but widespread changes provide a unique opportunity for studies using digital phenotyping tools. Digital phenotyping tools, such as mobile passive monitoring platforms (MPM), provide a new perspective on human behavior and hold promise to improve human behavioral research. However, there is currently little evidence that these tools can reliably detect changes in behavior. Considering the Considering the COVID-19 pandemic as a high impact common environmental factor we studied potential impact on behavior of participants using our mobile passive monitoring platform BEHAPP that was ambulatory tracking them during the COVID-19 pandemic. We pooled data from three MPM studies involving Schizophrenia (SZ), Major Depressive Disorder (MDD) and Bipolar Disorder (BD) patients (N = 12). We compared the data collected on weekdays during three weeks prior and three weeks subsequent to the start of the quarantine. We hypothesized an increase in communication and a decrease in mobility. We observed a significant increase in the total time spent on communication applications (median 179 and 243 min per week respectively, p = 0.005), and a significant decrease in the number of unique places visited (median 6 and 3 visits per week respectively, p = 0.007), while the total time spent at home did not change significantly (median 64 and 77 h per week, respectively, p = 0.594). The data provides a proof of principle that digital phenotyping tools can identify changes in human behavior incited by a common external environmental factor., Competing Interests: Conflict of Interest Authors declare no conflicts of interest., (Copyright © 2020. Published by Elsevier B.V.)

Anorexia nervosa (AN) and obsessive-compulsive disorder (OCD) are often comorbid and likely to share genetic risk factors. Hence, we examine their shared genetic background using a cross-disorder GWAS meta-analysis of 3495 AN cases, 2688 OCD cases, and 18,013 controls. We confirmed a high genetic correlation between AN and OCD (r g  = 0.49 ± 0.13, p = 9.07 × 10 -7 ) and a sizable SNP heritability (SNP h 2  = 0.21 ± 0.02) for the cross-disorder phenotype. Although no individual loci reached genome-wide significance, the cross-disorder phenotype showed strong positive genetic correlations with other psychiatric phenotypes (e.g., r g  = 0.36 with bipolar disorder and 0.34 with neuroticism) and negative genetic correlations with metabolic phenotypes (e.g., r g  = -0.25 with body mass index and -0.20 with triglycerides). Follow-up analyses revealed that although AN and OCD overlap heavily in their shared risk with other psychiatric phenotypes, the relationship with metabolic and anthropometric traits is markedly stronger for AN than for OCD. We further tested whether shared genetic risk for AN/OCD was associated with particular tissue or cell-type gene expression patterns and found that the basal ganglia and medium spiny neurons were most enriched for AN-OCD risk, consistent with neurobiological findings for both disorders. Our results confirm and extend genetic epidemiological findings of shared risk between AN and OCD and suggest that larger GWASs are warranted.

The use of smartphone-based location data to quantify behavior longitudinally and passively is rapidly gaining traction in neuropsychiatric research. However, a standardized and validated preprocessing framework for deriving behavioral phenotypes from smartphone-based location data is currently lacking. Here, we present a preprocessing framework consisting of methods that are validated in the context of geospatial data. This framework aims to generate context-enriched location data by identifying stationary, non-stationary, and recurrent stationary states in movement patterns. Subsequently, this context-enriched data is used to derive a series of behavioral phenotypes that are related to movement. By using smartphone-based location data collected from 245 subjects, including patients with schizophrenia, we show that the proposed framework is effective and accurate in generating context-enriched location data. This data was subsequently used to derive behavioral readouts that were sensitive in detecting behavioral nuances related to schizophrenia and aging, such as the time spent at home and the number of unique places visited. Overall, our results indicate that the proposed framework reliably preprocesses raw smartphone-based location data in such a manner that relevant behavioral phenotypes of interest can be derived.

Context-dependent biological variation presents a unique challenge to the reproducibility of results in experimental animal research, because organisms' responses to experimental treatments can vary with both genotype and environmental conditions. In March 2019, experts in animal biology, experimental design and statistics convened in Blonay, Switzerland, to discuss strategies addressing this challenge. In contrast to the current gold standard of rigorous standardization in experimental animal research, we recommend the use of systematic heterogenization of study samples and conditions by actively incorporating biological variation into study design through diversifying study samples and conditions. Here we provide the scientific rationale for this approach in the hope that researchers, regulators, funders and editors can embrace this paradigm shift. We also present a road map towards better practices in view of improving the reproducibility of animal research.

Exposure to severe or persistent social stress may lead to the development of psychiatric disorders such as anxiety and depression. These mood disorders are associated with structural alterations of neural architecture in limbic brain regions that control emotion, mood and cognition. Structural remodeling may either be a sign of successful adaptation, or of failure to do so. In neuropsychiatric disorders like depression structural remodeling involves apoptosis, reduced neurogenesis, and structural remodeling of neuronal dendrites which most likely reflects the latter. Here we review key findings from animal models of psychosocial stress that have been used to gain insights into the relation between stress-related behavioral disorders like depression and structural plasticity. Specifically, we focus on models having a high face validity like social defeat stress in the resident-intruder paradigm and chronic stress of social subordination in social housing conditions. Moderate to severe social stress appears to stimulate plasticity and neuronal growth in regions of the amygdala, whereas the effects in the hippocampus and prefrontal cortex tend to be opposite. A major focus of the current review is to characterize social stress induced structural changes in these brain regions, aiming to provide insight in pathways and factors that underlie behavioral effects of stress and depression., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Inconsistent findings between laboratories are hampering scientific progress and are of increasing public concern. Differences in laboratory environment is a known factor contributing to poor reproducibility of findings between research sites, and well-controlled multisite efforts are an important next step to identify the relevant factors needed to reduce variation in study outcome between laboratories. Through harmonization of apparatus, test protocol, and aligned and non-aligned environmental variables, the present study shows that behavioral pharmacological responses in Shank2 knockout (KO) rats, a model of synaptic dysfunction relevant to autism spectrum disorders, were highly replicable across three research centers. All three sites reliably observed a hyperactive and repetitive behavioral phenotype in KO rats compared to their wild-type littermates as well as a dose-dependent phenotype attenuation following acute injections of a selective mGluR1 antagonist. These results show that reproducibility in preclinical studies can be obtained and emphasizes the need for high quality and rigorous methodologies in scientific research. Considering the observed external validity, the present study also suggests mGluR1 as potential target for the treatment of autism spectrum disorders.

Anorexia nervosa (AN) is an often chronic, difficult to treat illness that leads to brain volume reductions in gray and white matter. The underlying pathophysiology is poorly understood, despite its potential importance in explaining the neuropsychological deficits and clinical symptoms associated with the illness. We used the activity-based anorexia model (ABA), which includes food reduction and running wheel access in female rats to study brain changes after starvation and refeeding. Longitudinal animal MRI and post-mortem brain sections confirmed a reduction in the mean brain volumes of ABA animals compared to controls. In addition, the mean number of astrocytes was reduced by over 50% in the cerebral cortex and corpus callosum, while the mean number of neurons was unchanged. Furthermore, mean astrocytic GFAP mRNA expression was similarly reduced in the ABA animals, as was the mean cell proliferation rate, whereas the mean apoptosis rate did not increase. After refeeding, the starvation-induced effects were almost completely reversed. The observation of the astrocyte reduction in our AN animal model is an important new finding that could help explain starvation-induced neuropsychological changes in patients with AN. Astrocyte-targeted research and interventions could become a new focus for both AN research and therapy.

The human social brain is complex. Current knowledge fails to define the neurobiological processes underlying social behaviour involving the (patho-) physiological mechanisms that link system-level phenomena to the multiple hierarchies of brain function. Unfortunately, such a high complexity may also be associated with a high susceptibility to several pathogenic interventions. Consistently, social deficits sometimes represent the first signs of a number of neuropsychiatric disorders including schizophrenia (SCZ), Alzheimer's disease (AD) and major depressive disorder (MDD) which leads to a progressive social dysfunction. In the present review we summarize present knowledge linking neurobiological substrates sustaining social functioning, social dysfunction and social withdrawal in major psychiatric disorders. Interestingly, AD, SCZ, and MDD affect the social brain in similar ways. Thus, social dysfunction and its most evident clinical expression (i.e., social withdrawal) may represent an innovative transdiagnostic domain, with the potential of being an independent entity in terms of biological roots, with the perspective of targeted interventions., (Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Trans-diagnostic, domain- or symptom-focused approaches have been heralded as advancing psychiatric research, but relatively few clinical research programmes have been undertaken to leverage their potential. In this manuscript we describe the approach and protocol for an exploratory study, PRISM (Psychiatric Ratings using Intermediate Stratified Markers), that will be conducted to explore the biomarkers in schizophrenia (SZ) and Alzheimer's Disease (AD) that may be related to a common symptom, social withdrawal. Patient participants (N = 72 SZ and N = 72 AD study completers), will complete a series of fMRI, EEG, and behavioural paradigms, as well as contributing blood-derived (e.g. epigenetic) and smartphone data related to social behaviour. Self- as well as caregiver- and researcher-reported assessments will be provided to characterise social withdrawal. Normative data will also be collected from a group of healthy controls (N = 48 study completers), half of whom will be matched in terms of age and gender distribution to the SZ and AD group, respectively. Thus we will explore both differentiation and cross-diagnostic overlap in the biomarkers associated with different levels of social withdrawal in SZ and AD. In this way we aim to provide a deeper understanding of the biological underpinnings of symptomatology common to both disorders, and provide insights into novel treatment targets and future drug development approaches., (Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.)

The current nosology of neuropsychiatric disorders allows for a pragmatic approach to treatment choice, regulation and clinical research. However, without a biological rationale for these disorders, drug development has stagnated. The recently EU-funded PRISM project aims to develop a quantitative biological approach to the understanding and classification of neuropsychiatric diseases to accelerate the discovery and development of better treatments. By combining clinical data sets from major worldwide disease cohorts and by applying innovative technologies to deeply phenotype stratified patient groups, we will define a set of quantifiable biological parameters for social withdrawal and cognitive deficits common to Schizophrenia (SZ), Major Depression (MD), and Alzheimer's Disease (AD). These studies aim to provide new classification and assessment tools for social and cognitive performance across neuropsychiatric disorders, clinically relevant substrates for treatment development, and predictive, preclinical animal systems. With patients and regulatory agencies, we seek to provide clear routes for the future translation and regulatory approval for new treatments and provide solutions to the growing public health challenges of psychiatry and neurology., (Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Objectives: Severe grey and white matter volume reductions were found in patients with anorexia nervosa (AN) that were linked to neuropsychological deficits while their underlying pathophysiology remains unclear. For the first time, we analysed the cellular basis of brain volume changes in an animal model (activity-based anorexia, ABA)., Methods: Female rats had 24 h/day running wheel access and received reduced food intake until a 25% weight reduction was reached and maintained for 2 weeks., Results: In ABA rats, the volumes of the cerebral cortex and corpus callosum were significantly reduced compared to controls by 6% and 9%, respectively. The number of GFAP-positive astrocytes in these regions decreased by 39% and 23%, total astrocyte-covered area by 83% and 63%. In neurons no changes were observed. The findings were complemented by a 60% and 49% reduction in astrocyte (GFAP) mRNA expression., Conclusions: Volumetric brain changes in ABA animals mirror those in human AN patients. These alterations are associated with a reduction of GFAP-positive astrocytes as well as GFAP expression. Reduced astrocyte functioning could help explain neuronal dysfunctions leading to symptoms of rigidity and impaired learning. Astrocyte loss could constitute a new research target for understanding and treating semi-starvation and AN.

Background: Anorexia nervosa (AN) is often a chronic eating disorder characterised by body image disturbance and low body weight often associated with starvation-induced amenorrhoea and excessive exercise. Activity-based anorexia (ABA) is an animal model representing many somatic aspects of this psychiatric illness. We systematically manipulated the extent and length of starvation and animal age to find the optimal parameters to study chronic starvation., New Methods: Wistar rats had 24h/day running wheel access and received 40% of their baseline food intake until a 20% or 25% weight reduction was reached (acute starvation). This body weight was then maintained for two weeks (chronic starvation). The rats of different ages of 4 or 8 weeks were used to represent early and late adolescent animals, respectively. The complete absence of a menstrual cycle was defined as the primary outcome parameter., Results: Acute starvation caused a disruption of the oestrous cycle in 58% of the animals. During chronic starvation, a complete loss of the oestrous cycle could be found. Furthermore, 4-week-old rats exhibited higher levels of hyperactivity and amenorrhoea than 8-week-old animals. A 20% starvation level led to 90% loss of cycle, while a 25% starvation level triggered complete loss., Comparison With Existing Methods: Most current ABA models focus on acute starvation, while most patients are chronically ill., Conclusions: The optimal parameters to achieve complete amenorrhoea included early adolescence, chronic starvation and 25% weight loss. The new ABA model allows studying the effects of chronic AN on underlying behavioural, hormonal and brain pathobiology., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Animal studies provide a unique opportunity to study the consequences of genetic variants at the behavioural level. Human studies have identified hundreds of risk genes for autism spectrum disorder (ASD) that can lead to understanding on how genetic variation contributes to individual differences in social interaction and stereotyped behaviour in people with ASD. To develop rational therapeutic interventions, systematic animal model studies are needed to understand the relationships between genetic variation, pathogenic processes and the expression of autistic behaviours. Genetic and non-genetic animal model strategies are here reviewed in their propensity to study the underpinnings of behavioural trait variation. We conclude that an integration of reverse and forward genetic approaches may be essential to unravel the neurobiological mechanisms underlying ASD.

Autism spectrum disorder (ASD) is a neurodevelopmental condition primarily characterised by alterations in social interaction and communication combined with the presence of restricted interests and stereotyped behaviours. Mutations in several genes have been associated with ASD resulting in the generation of corresponding mouse models. Here, we focus on the behavioural (social and stereotyped behaviours), functional and structural traits of mice with mutations in genes encoding defined synaptic proteins including adhesion proteins, scaffolding proteins and subunits of channels and receptors. A meta-analysis on ASD mouse models shows that they can be divided into two subgroups. Cluster I gathered models highly impaired in social interest, stereotyped behaviours, synaptic physiology and protein composition, while Cluster II regrouped much less impaired models, with typical social interactions. This distribution was not related to gene families. Even within the large panel of mouse models carrying mutations in Shank3, the number of mutated isoforms was not related to the severity of the phenotype. Our study points that the majority of structural or functional analyses were performed in the hippocampus. However, to robustly link the structural and functional impairments with the behavioural deficits observed, brain structures forming relevant nodes in networks involved in social and stereotyped behaviours should be targeted in the future. In addition, the characterisation of core ASD-like behaviours needs to be more detailed using new approaches quantifying the variations in social motivation, recognition and stereotyped behaviours.