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Bipolar disorder (BD) is a heritable mental illness with complex etiology. While the largest published genome-wide association study identified 64 BD risk loci, the causal SNPs and genes within these loci remain unknown. We applied a suite of statistical and functional fine-mapping methods to these loci, and prioritized 22 likely causal SNPs for BD. We mapped these SNPs to genes, and investigated their likely functional consequences by integrating variant annotations, brain cell-type epigenomic annotations, brain quantitative trait loci, and results from rare variant exome sequencing in BD. Convergent lines of evidence supported the roles of SCN2A, TRANK1, DCLK3, INSYN2B, SYNE1, THSD7A, CACNA1B, TUBBP5, PLCB3, PRDX5, KCNK4, AP001453.3, TRPT1, FKBP2, DNAJC4, RASGRP1, FURIN, FES, YWHAE, DPH1, GSDMB, MED24, THRA, EEF1A2, and KCNQ2 in BD. These represent promising candidates for functional experiments to understand biological mechanisms and therapeutic potential. Additionally, we demonstrated that fine-mapping effect sizes can improve performance and transferability of BD polygenic risk scores across ancestrally diverse populations, and present a high-throughput fine-mapping pipeline (https://github.com/mkoromina/SAFFARI).
Investigators in the cognitive neurosciences have turned to Big Data to address persistent replication and reliability issues by increasing sample sizes, statistical power, and representativeness of data. While there is tremendous potential to advance science through open data sharing, these efforts unveil a host of new questions about how to integrate data arising from distinct sources and instruments. We focus on the most frequently assessed area of cognition - memory testing - and demonstrate a process for reliable data harmonization across three common measures. We aggregated raw data from 53 studies from around the world which measured at least one of three distinct verbal learning tasks, totaling N = 10,505 healthy and brain-injured individuals. A mega analysis was conducted using empirical bayes harmonization to isolate and remove site effects, followed by linear models which adjusted for common covariates. After corrections, a continuous item response theory (IRT) model estimated each individual subject’s latent verbal learning ability while accounting for item difficulties. Harmonization significantly reduced inter-site variance by 37% while preserving covariate effects. The effects of age, sex, and education on scores were found to be highly consistent across memory tests. IRT methods for equating scores across AVLTs agreed with held-out data of dually-administered tests, and these tools are made available for free online. This work demonstrates that large-scale data sharing and harmonization initiatives can offer opportunities to address reproducibility and integration challenges across the behavioral sciences.
A webinar series that was organised by the Academy of Pharmaceutical Sciences Biopharmaceutics focus group in 2021 focused on the challenges of developing clinically relevant dissolution specifications (CRDSs) for oral drug products. Industrial scientists, together with regulatory and academic scientists, came together through a series of six webinars, to discuss progress in the field, emerging trends, and areas for continued collaboration and harmonisation. Each webinar also hosted a Q&A session where participants could discuss the shared topic and information. Although it was clear from the presentations and Q&A sessions that we continue to make progress in the field of CRDSs and the utility/success of PBBM, there is also a need to continue the momentum and dialogue between the industry and regulators. Five key areas were identified which require further discussion and harmonisation.
Nowadays, several options are available to treat patients with conductive or mixed hearing loss. Whenever surgical intervention is not possible or contra-indicated, and amplification by a conventional hearing device (e.g., behind-the-ear device) is not feasible, then implantable hearing devices are an indispensable next option. Implantable bone-conduction devices and middle-ear implants have advantages but also limitations concerning complexity/invasiveness of the surgery, medical complications, and effectiveness. To counsel the patient, the clinician should have a good overview of the options with regard to safety and reliability as well as unequivocal technical performance data. The present consensus document is the outcome of an extensive iterative process including ENT specialists, audiologists, health-policy scientists, and representatives/technicians of the main companies in this field. This document should provide a first framework for procedures and technical characterization to enhance effective communication between these stakeholders, improving health care.
Chimeric antigen receptor (CAR) T cell therapy is a potent new treatment option for relapsed or refractory hematologic malignancies. As the monitoring of CAR T cell kinetics can provide insights into the activity of the therapy, appropriate CAR T cell detection methods are essential. Here, we report on the comprehensive validation of a flow cytometric assay for peripheral blood CD19 CAR T cell detection. Further, a retrospective analysis (n = 30) of CAR T cell and B cell levels over time has been performed, and CAR T cell phenotypes have been characterized. Serial dilution experiments demonstrated precise and linear quantification down to 0.05% of T cells or 22 CAR T cell events. The calculated detection limit at 13 events was confirmed with CAR T cell negative control samples. Inter-method comparison with real-time PCR showed appreciable correlation. Stability testing revealed diminished CAR T cell values already one day after sample collection. While we found long-term CAR T cell detectability and B cell aplasia in most patients (12/17), some patients (5/17) experienced B cell recovery. In three of these patients the coexistence of CAR T cells and regenerating B cells was observed. Repeat CAR T cell infusions led to detectable but limited re-expansions. Comparison of CAR T cell subsets with their counterparts among all T cells showed a significantly higher percentage of effector memory T cells and a significantly lower percentage of naïve T cells and T EMRA cells among CAR T cells. In conclusion, flow cytometric CAR T cell detection is a reliable method to monitor CAR T cells if measurements start without delay and sufficient T cell counts are given.
Cardiac rehabilitation (CR) is a multidisciplinary intervention including patient assessment and medical actions to promote stabilization, management of cardiovascular risk factors, vocational support, psychosocial management, physical activity counselling, and prescription of exercise training. Millions of people with cardiac implantable electronic devices live in Europe and their numbers are progressively increasing, therefore, large subsets of patients admitted in CR facilities have a cardiac implantable electronic device. Patients who are cardiac implantable electronic devices recipients are considered eligible for a CR programme. This is not only related to the underlying heart disease but also to specific issues, such as psychological adaptation to living with an implanted device and, in implantable cardioverter-defibrillator patients, the risk of arrhythmia, syncope, and sudden cardiac death. Therefore, these patients should receive special attention, as their needs may differ from other patients participating in CR. As evidence from studies of CR in patients with cardiac implantable electronic devices is sparse, detailed clinical practice guidelines are lacking. Here, we aim to provide practical recommendations for CR in cardiac implantable electronic devices recipients in order to increase CR implementation, efficacy, and safety in this subset of patients.
The entorhino-dentate projection, i.e., the perforant pathway, terminates in a highly ordered and laminated fashion in the rodent dentate gyrus (DG): fibers arising from the medial entorhinal cortex (MEC) terminate in the middle molecular layer, whereas fibers arising from the lateral entorhinal cortex (LEC) terminate in the outer molecular layer of the DG. In rats and rabbits, a crossed entorhino-dentate projection exists, which originates from the entorhinal cortex (EC) and terminates in the contralateral DG. In contrast, in mice, such a crossed projection is reportedly absent. Using single and double mouse organotypic entorhino-hippocampal slice cultures, we studied the ipsi- and crossed entorhino-dentate projections. Viral tracing revealed that entorhino-dentate projections terminate with a high degree of lamina-specificity in single as well as in double cultures. Furthermore, in double cultures, entorhinal axons arising from one slice freely intermingled with entorhinal axons originating from the other slice. In single as well as in double cultures, entorhinal axons exhibited a correct topographical projection to the DG: medial entorhinal axons terminated in the middle and lateral entorhinal axons terminated in the outer molecular layer. Finally, entorhinal neurons were virally transduced with Channelrhodopsin2-YFP and stimulated with light, revealing functional connections between the EC and dentate granule cells. We conclude from our findings that entorhino-dentate projections form bilaterally in the mouse hippocampus in vitro and that the mouse DG provides a permissive environment for crossed entorhinal fibers.
Objective To explore factors that potentially impact external validation performance while developing and validating a prognostic model for hospital admissions (HAs) in complex older general practice patients.
Study design and setting Using individual participant data from four cluster-randomised trials conducted in the Netherlands and Germany, we used logistic regression to develop a prognostic model to predict all-cause HAs within a 6-month follow-up period. A stratified intercept was used to account for heterogeneity in baseline risk between the studies. The model was validated both internally and by using internal-external cross-validation (IECV).
Results Prior HAs, physical components of the health-related quality of life comorbidity index, and medication-related variables were used in the final model. While achieving moderate discriminatory performance, internal bootstrap validation revealed a pronounced risk of overfitting. The results of the IECV, in which calibration was highly variable even after accounting for between-study heterogeneity, agreed with this finding. Heterogeneity was equally reflected in differing baseline risk, predictor effects and absolute risk predictions.
Conclusions Predictor effect heterogeneity and differing baseline risk can explain the limited external performance of HA prediction models. With such drivers known, model adjustments in external validation settings (eg, intercept recalibration, complete updating) can be applied more purposefully.
Trial registration number PROSPERO id: CRD42018088129.
Background: Cumulative anticholinergic exposure, also known as anticholinergic burden, is associated with a variety of adverse outcomes. However, studies show that anticholinergic effects tend to be underestimated by prescribers, and anticholinergics are the most frequently prescribed potentially inappropriate medication in older patients. The grading systems and drugs included in existing scales to quantify anticholinergic burden differ considerably and do not adequately account for patients’ susceptibility to medications. Furthermore, their ability to link anticholinergic burden with adverse outcomes such as falls is unclear. This study aims to develop a prognostic model that predicts falls in older general practice patients, to assess the performance of several anticholinergic burden scales, and to quantify the added predictive value of anticholinergic symptoms in this context.
Methods: Data from two cluster-randomized controlled trials investigating medication optimization in older general practice patients in Germany will be used. One trial (RIME, n = 1,197) will be used for the model development and the other trial (PRIMUM, n = 502) will be used to externally validate the model. A priori, candidate predictors will be selected based on a literature search, predictor availability, and clinical reasoning. Candidate predictors will include socio-demographics (e.g. age, sex), morbidity (e.g. single conditions), medication (e.g. polypharmacy, anticholinergic burden as defined by scales), and well-being (e.g. quality of life, physical function). A prognostic model including sociodemographic and lifestyle-related factors, as well as variables on morbidity, medication, health status, and well-being, will be developed, whereby the prognostic value of extending the model to include additional patient-reported symptoms will be also assessed. Logistic regression will be used for the binary outcome, which will be defined as “no falls” vs. “≥1 fall” within six months of baseline, as reported in patient interviews. Discussion: As the ability of different anticholinergic burden scales to predict falls in older patients is unclear, this study may provide insights into their relative importance as well as into the overall contribution of anticholinergic symptoms and other patient characteristics. The results may support general practitioners in their clinical decision-making and in prescribing fewer medications with anticholinergic properties.