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Abstract Schizophrenia (SZ) is a severe psychiatric disorder, with a prevalence of 1–2% world-wide and substantial health- and social care costs. The pathology is influenced by both genetic and environmental factors, however the underlying cause still remains elusive. SZ has symptoms including delusions, hallucinations, confused thoughts, diminished emotional responses, social withdrawal and anhedonia. The onset of psychosis is usually in late adolescence or early adulthood. Multiple genome-wide association and whole exome sequencing studies have provided extraordinary insights into the genetic variants underlying familial as well as polygenic forms of the disease. Nonetheless, a major limitation in schizophrenia research remains the lack of clinically relevant animal models, which in turn hampers the development of novel effective therapies for the patients. The emergence of human induced pluripotent stem cell (hiPSC) technology has allowed researchers to work with SZ patient-derived neuronal and glial cell types in vitro and to investigate the molecular basis of the disorder in a human neuronal context. In this review, we summarise findings from available studies using hiPSC-based neural models and discuss how these have provided new insights into molecular and cellular pathways of SZ. Further, we highlight different examples of how these models have shown alterations in neurogenesis, neuronal maturation, neuronal connectivity and synaptic impairment as well as mitochondrial dysfunction and dysregulation of miRNAs in SZ patient-derived cultures compared to controls. We discuss the pros and cons of these models and describe the potential of using such models for deciphering the contribution of specific human neural cell types to the development of the disease.

Abstract Background General practitioners (GPs) should regularly review patients’ medications and, if necessary, deprescribe, as inappropriate polypharmacy may harm patients’ health. However, deprescribing can be challenging for physicians. This study investigates GPs’ deprescribing decisions in 31 countries. Methods In this case vignette study, GPs were invited to participate in an online survey containing three clinical cases of oldest-old multimorbid patients with potentially inappropriate polypharmacy. Patients differed in terms of dependency in activities of daily living (ADL) and were presented with and without history of cardiovascular disease (CVD). For each case, we asked GPs if they would deprescribe in their usual practice. We calculated proportions of GPs who reported they would deprescribe and performed a multilevel logistic regression to examine the association between history of CVD and level of dependency on GPs’ deprescribing decisions. Results Of 3,175 invited GPs, 54% responded (N = 1,706). The mean age was 50 years and 60% of respondents were female. Despite differences across GP characteristics, such as age (with older GPs being more likely to take deprescribing decisions), and across countries, overall more than 80% of GPs reported they would deprescribe the dosage of at least one medication in oldest-old patients (> 80 years) with polypharmacy irrespective of history of CVD. The odds of deprescribing was higher in patients with a higher level of dependency in ADL (OR =1.5, 95%CI 1.25 to 1.80) and absence of CVD (OR =3.04, 95%CI 2.58 to 3.57). Interpretation The majority of GPs in this study were willing to deprescribe one or more medications in oldest-old multimorbid patients with polypharmacy. Willingness was higher in patients with increased dependency in ADL and lower in patients with CVD.

Abstract Background Genome-wide association studies (GWAS) have identified several hundred susceptibility loci for type 2 diabetes (T2D). One critical, but unresolved, issue concerns the extent to which the mechanisms through which these diverse signals influencing T2D predisposition converge on a limited set of biological processes. However, the causal variants identified by GWAS mostly fall into a non-coding sequence, complicating the task of defining the effector transcripts through which they operate. Methods Here, we describe implementation of an analytical pipeline to address this question. First, we integrate multiple sources of genetic, genomic and biological data to assign positional candidacy scores to the genes that map to T2D GWAS signals. Second, we introduce genes with high scores as seeds within a network optimization algorithm (the asymmetric prize-collecting Steiner tree approach) which uses external, experimentally confirmed protein-protein interaction (PPI) data to generate high-confidence sub-networks. Third, we use GWAS data to test the T2D association enrichment of the “non-seed” proteins introduced into the network, as a measure of the overall functional connectivity of the network. Results We find (a) non-seed proteins in the T2D protein-interaction network so generated (comprising 705 nodes) are enriched for association to T2D (p = 0.0014) but not control traits, (b) stronger T2D-enrichment for islets than other tissues when we use RNA expression data to generate tissue-specific PPI networks and (c) enhanced enrichment (p = 3.9 × 10− 5) when we combine the analysis of the islet-specific PPI network with a focus on the subset of T2D GWAS loci which act through defective insulin secretion. Conclusions These analyses reveal a pattern of non-random functional connectivity between candidate causal genes at T2D GWAS loci and highlight the products of genes including YWHAG, SMAD4 or CDK2 as potential contributors to T2D-relevant islet dysfunction. The approach we describe can be applied to other complex genetic and genomic datasets, facilitating integration of diverse data types into disease-associated networks.

Abstract Background Cerebral edema can cause life-threatening increase in intracranial pressure. Besides surgical craniectomy performed in severe cases, osmotherapy may be employed to lower the intracranial pressure by osmotic extraction of cerebral fluid upon intravenous infusion of mannitol or NaCl. A so-called rebound effect can, however, hinder continuous reduction in cerebral fluid by yet unresolved mechanisms. Methods We determined the brain water and electrolyte content in healthy rats treated with osmotherapy. Osmotherapy (elevated plasma osmolarity) was mediated by intraperitoneal injection of NaCl or mannitol with inclusion of pharmacological inhibitors of selected ion-transporters present at the capillary lumen or choroidal membranes. Brain barrier integrity was determined by fluorescence detection following intravenous delivery of Na+-fluorescein. Results NaCl was slightly more efficient than mannitol as an osmotic agent. The brain water loss was only ~ 60% of that predicted from ideal osmotic behavior, which could be accounted for by cerebral Na+ and Cl− accumulation. This electrolyte accumulation represented the majority of the rebound response, which was unaffected by the employed pharmacological agents. The brain barriers remained intact during the elevated plasma osmolarity. Conclusions A brain volume regulatory response occurs during osmotherapy, leading to the rebound response. This response involves brain accumulation of Na+ and Cl− and takes place by unresolved molecular mechanisms that do not include the common ion-transporting mechanisms located in the capillary endothelium at the blood–brain barrier and in the choroid plexus epithelium at the blood–CSF barrier. Future identification of these ion-transporting routes could provide a pharmacological target to prevent the rebound effect associated with the widely used osmotherapy.

Abstract Background Integrating rare variation from trio family and case–control studies has successfully implicated specific genes contributing to risk of neurodevelopmental disorders (NDDs) including autism spectrum disorders (ASD), intellectual disability (ID), developmental disorders (DDs), and epilepsy (EPI). For schizophrenia (SCZ), however, while sets of genes have been implicated through the study of rare variation, only two risk genes have been identified. Methods We used hierarchical Bayesian modeling of rare-variant genetic architecture to estimate mean effect sizes and risk-gene proportions, analyzing the largest available collection of whole exome sequence data for SCZ (1,077 trios, 6,699 cases, and 13,028 controls), and data for four NDDs (ASD, ID, DD, and EPI; total 10,792 trios, and 4,058 cases and controls). Results For SCZ, we estimate there are 1,551 risk genes. There are more risk genes and they have weaker effects than for NDDs. We provide power analyses to predict the number of risk-gene discoveries as more data become available. We confirm and augment prior risk gene and gene set enrichment results for SCZ and NDDs. In particular, we detected 98 new DD risk genes at FDR < 0.05. Correlations of risk-gene posterior probabilities are high across four NDDs (ρ>0.55), but low between SCZ and the NDDs (ρ

Abstract Background In oldest-old patients (>80), few trials showed efficacy of treating hypertension and they included mostly the healthiest elderly. The resulting lack of knowledge has led to inconsistent guidelines, mainly based on systolic blood pressure (SBP), cardiovascular disease (CVD) but not on frailty despite the high prevalence in oldest-old. This may lead to variation how General Practitioners (GPs) treat hypertension. Our aim was to investigate treatment variation of GPs in oldest-olds across countries and to identify the role of frailty in that decision. Methods Using a survey, we compared treatment decisions in cases of oldest-old varying in SBP, CVD, and frailty. GPs were asked if they would start antihypertensive treatment in each case. In 2016, we invited GPs in Europe, Brazil, Israel, and New Zealand. We compared the percentage of cases that would be treated per countries. A logistic mixed-effects model was used to derive odds ratio (OR) for frailty with 95% confidence intervals (CI), adjusted for SBP, CVD, and GP characteristics (sex, location and prevalence of oldest-old per GP office, and years of experience). The mixed-effects model was used to account for the multiple assessments per GP. Results The 29 countries yielded 2543 participating GPs: 52% were female, 51% located in a city, 71% reported a high prevalence of oldest-old in their offices, 38% and had >20 years of experience. Across countries, considerable variation was found in the decision to start antihypertensive treatment in the oldest-old ranging from 34 to 88%. In 24/29 (83%) countries, frailty was associated with GPs’ decision not to start treatment even after adjustment for SBP, CVD, and GP characteristics (OR 0.53, 95%CI 0.48–0.59; ORs per country 0.11–1.78). Conclusions Across countries, we found considerable variation in starting antihypertensive medication in oldest-old. The frail oldest-old had an odds ratio of 0.53 of receiving antihypertensive treatment. Future hypertension trials should also include frail patients to acquire evidence on the efficacy of antihypertensive treatment in oldest-old patients with frailty, with the aim to get evidence-based data for clinical decision-making.