DNA methylation has been traditionally viewed as a highly stable epigenetic mark in post-mitotic cells, however, postnatal brains appear to exhibit stimulus-induced methylation changes, at least in a few identified CpG dinucleotides. How extensively the neuronal DNA methylome is regulated by neuronal activity is unknown. Using a next-generation sequencing-based method for genome-wide analysis at a single-nucleotide resolution, we quantitatively compared the CpG methylation landscape of adult mouse dentate granule neurons in vivo before and after synchronous neuronal activation. About 1.4% of 219,991 CpGs measured show rapid active demethylation or de novo methylation. Some modifications remain stable for at least 24 hours. These activity-modified CpGs exhibit a broad genomic distribution with significant enrichment in low-CpG density regions, and are associated with brain-specific genes related to neuronal plasticity. Our study implicates modification of the neuronal DNA methylome as a previously under-appreciated mechanism for activity-dependent epigenetic regulation in the adult nervous system.

Multiple EHR components provide a more consistent and higher performance than a single one for the selected phenotypes. We suggest considering multiple EHR components for future phenotyping design in order to obtain an ideal result.

Background Electronic health records (EHRs) are increasingly used for clinical and translational research through the creation of phenotype algorithms. Currently, phenotype algorithms are most commonly represented as noncomputable descriptive documents and knowledge artifacts that detail the protocols for querying diagnoses, symptoms, procedures, medications, and/or text-driven medical concepts, and are primarily meant for human comprehension. We present desiderata for developing a computable phenotype representation model (PheRM).Methods A team of clinicians and informaticians reviewed common features for multisite phenotype algorithms published in PheKB.org and existing phenotype representation platforms. We also evaluated well-known diagnostic criteria and clinical decision-making guidelines to encompass a broader category of algorithms.Results We propose 10 desired characteristics for a flexible, computable PheRM: (1) structure clinical data into queryable forms; (2) recommend use of a common data model, but also support customization for the variability and availability of EHR data among sites; (3) support both human-readable and computable representations of phenotype algorithms; (4) implement set operations and relational algebra for modeling phenotype algorithms; (5) represent phenotype criteria with structured rules; (6) support defining temporal relations between events; (7) use standardized terminologies and ontologies, and facilitate reuse of value sets; (8) define representations for text searching and natural language processing; (9) provide interfaces for external software algorithms; and (10) maintain backward compatibility.Conclusion A computable PheRM is needed for true phenotype portability and reliability across different EHR products and healthcare systems. These desiderata are a guide to inform the establishment and evolution of EHR phenotype algorithm authoring platforms and languages.

Rapid impulse propagation in the heart is a defining property of pectinated atrial myocardium (PAM) and the ventricular conduction system (VCS) and is essential for maintaining normal cardiac rhythm and optimal cardiac output. Conduction defects in these tissues produce a disproportionate burden of arrhythmic disease and are major predictors of mortality in heart failure patients. Despite the clinical importance, little is known about the gene regulatory network that dictates the fast conduction phenotype. Here, we have used signal transduction and transcriptional profiling screens to identify a genetic pathway that converges on the NRG1-responsive transcription factor ETV1 as a critical regulator of fast conduction physiology for PAM and VCS cardiomyocytes. Etv1 was highly expressed in murine PAM and VCS cardiomyocytes, where it regulates expression of Nkx2-5, Gja5, and Scn5a, key cardiac genes required for rapid conduction. Mice deficient in Etv1 exhibited marked cardiac conduction defects coupled with developmental abnormalities of the VCS. Loss of Etv1 resulted in a complete disruption of the normal sodium current heterogeneity that exists between atrial, VCS, and ventricular myocytes. Lastly, a phenome-wide association study identified a link between ETV1 and bundle branch block and heart block in humans. Together, these results identify ETV1 as a critical factor in determining fast conduction physiology in the heart.

Automated methotrexate-induced liver toxicity phenotype discovery for patients with RA based on structured and unstructured information in the EMR shows accurate results. Our work demonstrates that adding temporal features significantly improved classification results.