Quantitative neurosymptomatics: Linking quantitative biology to neuropsychiatry

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A quantitative approach to neuropsychiatry: The why and the how

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

Трехкоординатный пьезокерамический сканер на биморфных пьезо-элементах для зондового наномикроскопа

Предложена и исследована конструкция пьезокерамического сканера для наномикроскопов на основе диморфных пьезоэлементов. Построена и исследована модель сканера при помощи программы MicroCap 7.0

Social dysfunction is transdiagnostically associated with default mode network dysconnectivity in schizophrenia and Alzheimer’s disease

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 (pcorrected 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 (pcorrected =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 behaviourThe project leading to this application has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No 115916. This Joint Undertaking receives support from the European Union’s Horizon 2020 research and innovation programme and EFPIA. This publication reflects only the author’s views and neither the IMI 2JU nor EFPIA nor the European Commission are liable for any use that may be made of the information contained therei

Social brain, social dysfunction and social withdrawal

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

Effect of disease related biases on the subjective assessment of social functioning in Alzheimer's disease and schizophrenia patients

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.The PRISM project (www.prism-project.eu) leading to this application has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No 115916. This Joint Undertaking receives support from the European Union’s Horizon 2020 research and innovation programme and EFPIA. This publication reflects only the authors’ views neither IMI JU nor EFPIA nor the European Commission are liable for any use that may be made of the information contained therein. Dr. Arango has also received funding support by the Spanish Ministry of Science and Innovation. Instituto de Salud Carlos III (SAM16PE07CP1, PI16/02012, PI19/024), co-financed by ERDF Funds from the European Commission, “A way of making Europe”, CIBERSAM. Madrid Regional Government (B2017/BMD-3740 AGES-CM-2), European Union Structural Funds. Fundación Familia Alonso and Fundación Alicia Koplowit

Genetic underpinnings of sociability in the general population

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.Stress-related psychiatric disorders across the life spa

Relationships between social withdrawal and facial emotion recognition in neuropsychiatric disorders

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 emotionalcognitive bias that may impact social functioning in people with severe mental illness.Education and Child Studie