Modeling Disease Severity in Multiple Sclerosis Using Electronic Health Records

Objective: To optimally leverage the scalability and unique features of the electronic health records (EHR) for research that would ultimately improve patient care, we need to accurately identify patients and extract clinically meaningful measures. Using multiple sclerosis (MS) as a proof of principle, we showcased how to leverage routinely collected EHR data to identify patients with a complex neurological disorder and derive an important surrogate measure of disease severity heretofore only available in research settings. Methods: In a cross-sectional observational study, 5,495 MS patients were identified from the EHR systems of two major referral hospitals using an algorithm that includes codified and narrative information extracted using natural language processing. In the subset of patients who receive neurological care at a MS Center where disease measures have been collected, we used routinely collected EHR data to extract two aggregate indicators of MS severity of clinical relevance multiple sclerosis severity score (MSSS) and brain parenchymal fraction (BPF, a measure of whole brain volume). Results: The EHR algorithm that identifies MS patients has an area under the curve of 0.958, 83% sensitivity, 92% positive predictive value, and 89% negative predictive value when a 95% specificity threshold is used. The correlation between EHR-derived and true MSSS has a mean R[superscript 2] = 0.38±0.05, and that between EHR-derived and true BPF has a mean R[superscript 2] = 0.22±0.08. To illustrate its clinical relevance, derived MSSS captures the expected difference in disease severity between relapsing-remitting and progressive MS patients after adjusting for sex, age of symptom onset and disease duration (p = 1.56×10[superscript −12]). Conclusion: Incorporation of sophisticated codified and narrative EHR data accurately identifies MS patients and provides estimation of a well-accepted indicator of MS severity that is widely used in research settings but not part of the routine medical records. Similar approaches could be applied to other complex neurological disorders.National Institute of General Medical Sciences (U.S.) (NIH U54-LM008748

Use of Electronic Health Records to Support a Public Health Response to the COVID-19 Pandemic in the United States: A Perspective from Fifteen Academic Medical Centers

Our goal is to summarize the collective experience of 15 organizations in dealing with uncoordinated efforts that result in unnecessary delays in understanding, predicting, preparing for, containing, and mitigating the COVID-19 pandemic in the US. Response efforts involve the collection and analysis of data corresponding to healthcare organizations, public health departments, socioeconomic indicators, as well as additional signals collected directly from individuals and communities. We focused on electronic health record (EHR) data, since EHRs can be leveraged and scaled to improve clinical care, research, and to inform public health decision-making. We outline the current challenges in the data ecosystem and the technology infrastructure that are relevant to COVID-19, as witnessed in our 15 institutions. The infrastructure includes registries and clinical data networks to support population-level analyses. We propose a specific set of strategic next steps to increase interoperability, overall organization, and efficiencie

Genome-Wide Analysis Reveals a Major Role in Cell Fate Maintenance and an Unexpected Role in Endoreduplication for the Drosophila FoxA Gene Fork Head

Transcription factors drive organogenesis, from the initiation of cell fate decisions to the maintenance and implementation of these decisions. The Drosophila embryonic salivary gland provides an excellent platform for unraveling the underlying transcriptional networks of organ development because Drosophila is relatively unencumbered by significant genetic redundancy. The highly conserved FoxA family transcription factors are essential for various aspects of organogenesis in all animals that have been studied. Here, we explore the role of the single Drosophila FoxA protein Fork head (Fkh) in salivary gland organogenesis using two genome-wide strategies. A large-scale in situ hybridization analysis reveals a major role for Fkh in maintaining the salivary gland fate decision and controlling salivary gland physiological activity, in addition to its previously known roles in morphogenesis and survival. The majority of salivary gland genes (59%) are affected by fkh loss, mainly at later stages of salivary gland development. We show that global expression of Fkh cannot drive ectopic salivary gland formation. Thus, unlike the worm FoxA protein PHA-4, Fkh does not function to specify cell fate. In addition, Fkh only indirectly regulates many salivary gland genes, which is also distinct from the role of PHA-4 in organogenesis. Our microarray analyses reveal unexpected roles for Fkh in blocking terminal differentiation and in endoreduplication in the salivary gland and in other Fkh-expressing embryonic tissues. Overall, this study demonstrates an important role for Fkh in determining how an organ preserves its identity throughout development and provides an alternative paradigm for how FoxA proteins function in organogenesis

Estrogen Receptor β-Selective Agonists Stimulate Calcium Oscillations in Human and Mouse Embryonic Stem Cell-Derived Neurons

Estrogens are used extensively to treat hot flashes in menopausal women. Some of the beneficial effects of estrogens in hormone therapy on the brain might be due to nongenomic effects in neurons such as the rapid stimulation of calcium oscillations. Most studies have examined the nongenomic effects of estrogen receptors (ER) in primary neurons or brain slices from the rodent brain. However, these cells can not be maintained continuously in culture because neurons are post-mitotic. Neurons derived from embryonic stem cells could be a potential continuous, cell-based model to study nongenomic actions of estrogens in neurons if they are responsive to estrogens after differentiation. In this study ER-subtype specific estrogens were used to examine the role of ERα and ERβ on calcium oscillations in neurons derived from human (hES) and mouse embryonic stem cells. Unlike the undifferentiated hES cells the differentiated cells expressed neuronal markers, ERβ, but not ERα. The non-selective ER agonist 17β-estradiol (E2) rapidly increased [Ca2+]i oscillations and synchronizations within a few minutes. No change in calcium oscillations was observed with the selective ERα agonist 4,4′,4″-(4-Propyl-[1H]-pyrazole-1,3,5-triyl)trisphenol (PPT). In contrast, the selective ERβ agonists, 2,3-bis(4-Hydroxyphenyl)-propionitrile (DPN), MF101, and 2-(3-fluoro-4-hydroxyphenyl)-7-vinyl-1,3 benzoxazol-5-ol (ERB-041; WAY-202041) stimulated calcium oscillations similar to E2. The ERβ agonists also increased calcium oscillations and phosphorylated PKC, AKT and ERK1/2 in neurons derived from mouse ES cells, which was inhibited by nifedipine demonstrating that ERβ activates L-type voltage gated calcium channels to regulate neuronal activity. Our results demonstrate that ERβ signaling regulates nongenomic pathways in neurons derived from ES cells, and suggest that these cells might be useful to study the nongenomic mechanisms of estrogenic compounds

Global Analysis of Extracytoplasmic Stress Signaling in Escherichia coli

The Bae, Cpx, Psp, Rcs, and σE pathways constitute the Escherichia coli signaling systems that detect and respond to alterations of the bacterial envelope. Contributions of these systems to stress response have previously been examined individually; however, the possible interconnections between these pathways are unknown. Here we investigate the dynamics between the five stress response pathways by determining the specificities of each system with respect to signal-inducing conditions, and monitoring global transcriptional changes in response to transient overexpression of each of the effectors. Our studies show that different extracytoplasmic stress conditions elicit a combined response of these pathways. Involvement of the five pathways in the various tested stress conditions is explained by our unexpected finding that transcriptional responses induced by the individual systems show little overlap. The extracytoplasmic stress signaling pathways in E. coli thus regulate mainly complementary functions whose discrete contributions are integrated to mount the full adaptive response

Endocrinologic, neurologic, and visual morbidity after treatment for craniopharyngioma

Craniopharyngiomas are locally aggressive tumors which typically are focused in the sellar and suprasellar region near a number of critical neural and vascular structures mediating endocrinologic, behavioral, and visual functions. The present study aims to summarize and compare the published literature regarding morbidity resulting from treatment of craniopharyngioma. We performed a comprehensive search of the published English language literature to identify studies publishing outcome data of patients undergoing surgery for craniopharyngioma. Comparisons of the rates of endocrine, vascular, neurological, and visual complications were performed using Pearson’s chi-squared test, and covariates of interest were fitted into a multivariate logistic regression model. In our data set, 540 patients underwent surgical resection of their tumor. 138 patients received biopsy alone followed by some form of radiotherapy. Mean overall follow-up for all patients in these studies was 54 ± 1.8 months. The overall rate of new endocrinopathy for all patients undergoing surgical resection of their mass was 37% (95% CI = 33–41). Patients receiving GTR had over 2.5 times the rate of developing at least one endocrinopathy compared to patients receiving STR alone or STR + XRT (52 vs. 19 vs. 20%, χ2P < 0.00001). On multivariate analysis, GTR conferred a significant increase in the risk of endocrinopathy compared to STR + XRT (OR = 3.45, 95% CI = 2.05–5.81, P < 0.00001), after controlling for study size and the presence of significant hypothalamic involvement. There was a statistical trend towards worse visual outcomes in patients receiving XRT after STR compared to GTR or STR alone (GTR = 3.5% vs. STR 2.1% vs. STR + XRT 6.4%, P = 0.11). Given the difficulty in obtaining class 1 data regarding the treatment of this tumor, this study can serve as an estimate of expected outcomes for these patients, and guide decision making until these data are available

EU/US/CTAD Task Force: Lessons Learned from Recent and Current Alzheimer's Prevention Trials

At a meeting of the EU/US/Clinical Trials in Alzheimer’s Disease (CTAD) Task Force in December 2016, an international group of investigators from industry, academia, and regulatory agencies reviewed lessons learned from ongoing and planned prevention trials, which will help guide future clinical trials of AD treatments, particularly in the pre-clinical space. The Task Force discussed challenges that need to be addressed across all aspects of clinical trials, calling for innovation in recruitment and retention, infrastructure development, and the selection of outcome measures. While cognitive change provides a marker of disease progression across the disease continuum, there remains a need to identify the optimal assessment tools that provide clinically meaningful endpoints. Patient- and informant-reported assessments of cognition and function may be useful but present additional challenges. Imaging and other biomarkers are also essential to maximize the efficiency of and the information learned from clinical trials

Collaborative efforts to prevent Alzheimer’s disease

International audienc

Biomarkers for Alzheimer's disease therapeutic trials

© 2010 Elsevier Ltd. All rights reservedThe development of disease-modifying treatments for Alzheimer's disease requires innovative trials with large numbers of subjects and long observation periods. The use of blood, cerebrospinal fluid or neuroimaging biomarkers is critical for the demonstration of disease-modifying therapy effects on the brain. Suitable biomarkers are those which reflect the progression of AD related molecular mechanisms and neuropathology, including amyloidogenic processing and aggregation, hyperphosphorylation, accumulation of tau and neurofibrillary tangles, progressive functional, metabolic and structural decline, leading to neurodegeneration, loss of brain tissue and cognitive symptoms. Biomarkers should be used throughout clinical trial phases I–III of AD drug development. They can be used to enhance inclusion and exclusion criteria, or as baseline predictors to increase the statistical power of trials. Validated and qualified biomarkers may be used as outcome measures to detect treatment effects in pivotal clinical trials. Finally, biomarkers can be used to identify adverse effects. Questions regarding which biomarkers should be used in clinical trials, and how, are currently far from resolved. The Oxford Task Force continues and expands the work of our previous international expert task forces on disease-modifying trials and on endpoints for Alzheimer's disease clinical trials. The aim of this initiative was to bring together a selected number of key international opinion leaders and experts from academia, regulatory agencies and industry to condense the current knowledge and state of the art regarding the best use of biological markers in Alzheimer's disease therapy trials and to propose practical recommendations for the planning of future AD trials.GW was partly funded by the NIHR Biomedical Research Center Programme, Oxford, UK