An approach for collaborative development of a federated biomedical knowledge graph-based question-answering system: Question-of-the-Month challenges

Knowledge graphs have become a common approach for knowledge representation. Yet, the application of graph methodology is elusive due to the sheer number and complexity of knowledge sources. In addition, semantic incompatibilities hinder efforts to harmonize and integrate across these diverse sources. As part of The Biomedical Translator Consortium, we have developed a knowledge graph-based question-answering system designed to augment human reasoning and accelerate translational scientific discovery: the Translator system. We have applied the Translator system to answer biomedical questions in the context of a broad array of diseases and syndromes, including Fanconi anemia, primary ciliary dyskinesia, multiple sclerosis, and others. A variety of collaborative approaches have been used to research and develop the Translator system. One recent approach involved the establishment of a monthly "Question-of-the-Month (QotM) Challenge" series. Herein, we describe the structure of the QotM Challenge; the six challenges that have been conducted to date on drug-induced liver injury, cannabidiol toxicity, coronavirus infection, diabetes, psoriatic arthritis, and ATP1A3-related phenotypes; the scientific insights that have been gleaned during the challenges; and the technical issues that were identified over the course of the challenges and that can now be addressed to foster further development of the prototype Translator system. We close with a discussion on Large Language Models such as ChatGPT and highlight differences between those models and the Translator system.

Evaluating robustness of a generalized linear model when applied to electronic health record data accessed using an Open API

The Integrated Clinical and Environmental Exposures Service (ICEES) provides open regulatory-compliant access to clinical data, including electronic health record data, that have been integrated with environmental exposures data. While ICEES has been validated in the context of an asthma use case and several other use cases, the regulatory constraints on the ICEES open application programming interface (OpenAPI) result in data loss when using the service for multivariate analysis. In this study, we investigated the robustness of the ICEES OpenAPI through a comparative analysis, in which we applied a generalized linear model (GLM) to the OpenAPI data and the constraint-free source data to examine factors predictive of asthma exacerbations. Consistent with previous studies, we found that the main predictors identified by both analyses were sex, prednisone, race, obesity, and airborne particulate exposure. Comparison of GLM model fit revealed that data loss impacts model quality, but only with select interaction terms. We conclude that the ICEES OpenAPI supports multivariate analysis, albeit with potential data loss that users should be aware of.

Leveraging Open Electronic Health Record Data and Environmental Exposures Data to Derive Insights Into Rare Pulmonary Disease

Research on rare diseases has received increasing attention, in part due to the realized profitability of orphan drugs. Biomedical informatics holds promise in accelerating translational research on rare disease, yet challenges remain, including the lack of diagnostic codes for rare diseases and privacy concerns that prevent research access to electronic health records when few patients exist. The Integrated Clinical and Environmental Exposures Service (ICEES) provides regulatory-compliant open access to electronic health record data that have been integrated with environmental exposures data, as well as analytic tools to explore the integrated data. We describe a proof-of-concept application of ICEES to examine demographics, clinical characteristics, environmental exposures, and health outcomes among a cohort of patients enriched for phenotypes associated with cystic fibrosis (CF), idiopathic bronchiectasis (IB), and primary ciliary dyskinesia (PCD). We then focus on a subset of patients with CF, leveraging the availability of a diagnostic code for CF and serving as a benchmark for our development work. We use ICEES to examine select demographics, co-diagnoses, and environmental exposures that may contribute to poor health outcomes among patients with CF, defined as emergency department or inpatient visits for respiratory issues. We replicate current understanding of the pathogenesis and clinical manifestations of CF by identifying co-diagnoses of asthma, chronic nasal congestion, cough, middle ear disease, and pneumonia as factors that differentiate patients with poor health outcomes from those with better health outcomes. We conclude by discussing our preliminary findings in relation to other published work, the strengths and limitations of our approach, and our future directions.

Biolink Model: A universal schema for knowledge graphs in clinical, biomedical, and translational science

Within clinical, biomedical, and translational science, an increasing number of projects are adopting graphs for knowledge representation. Graph‐based data models elucidate the interconnectedness among core biomedical concepts, enable data structures to be easily updated, and support intuitive queries, visualizations, and inference algorithms. However, knowledge discovery across these “knowledge graphs” (KGs) has remained difficult. Data set heterogeneity and complexity; the proliferation of ad hoc data formats; poor compliance with guidelines on findability, accessibility, interoperability, and reusability; and, in particular, the lack of a universally accepted, open‐access model for standardization across biomedical KGs has left the task of reconciling data sources to downstream consumers. Biolink Model is an open‐source data model that can be used to formalize the relationships between data structures in translational science. It incorporates object‐oriented classification and graph‐oriented features. The core of the model is a set of hierarchical, interconnected classes (or categories) and relationships between them (or predicates) representing biomedical entities such as gene, disease, chemical, anatomic structure, and phenotype. The model provides class and edge attributes and associations that guide how entities should relate to one another. Here, we highlight the need for a standardized data model for KGs, describe Biolink Model, and compare it with other models. We demonstrate the utility of Biolink Model in various initiatives, including the Biomedical Data Translator Consortium and the Monarch Initiative, and show how it has supported easier integration and interoperability of biomedical KGs, bringing together knowledge from multiple sources and helping to realize the goals of translational science.

Progress toward a universal biomedical data translator

Clinical, biomedical, and translational science has reached an inflection point in the breadth and diversity of available data and the potential impact of such data to improve human health and well-being. However, the data are often siloed, disorganized, and not broadly accessible due to discipline-specific differences in terminology and representation. To address these challenges, the Biomedical Data Translator Consortium has developed and tested a pilot knowledge graph-based "Translator" system capable of integrating existing biomedical data sets and "translating" those data into insights intended to augment human reasoning and accelerate translational science. Having demonstrated feasibility of the Translator system, the Translator program has since moved into development, and the Translator Consortium has made significant progress in the research, design, and implementation of an operational system. Herein, we describe the current system's architecture, performance, and quality of results. We apply Translator to several real-world use cases developed in collaboration with subject-matter experts. Finally, we discuss the scientific and technical features of Translator and compare those features to other state-of-the-art, biomedical graph-based question-answering systems.

Development and Application of an Open Tool for Sharing and Analyzing Integrated Clinical and Environmental Exposures Data: Asthma Use Case

Background

The Integrated Clinical and Environmental Exposures Service (ICEES) serves as an open-source, disease-agnostic, regulatory-compliant framework and approach for openly exposing and exploring clinical data that have been integrated at the patient level with a variety of environmental exposures data. ICEES is equipped with tools to support basic statistical exploration of the integrated data in a completely open manner.

Objective

This study aims to further develop and apply ICEES as a novel tool for openly exposing and exploring integrated clinical and environmental data. We focus on an asthma use case.

Methods

We queried the ICEES open application programming interface (OpenAPI) using a functionality that supports chi-square tests between feature variables and a primary outcome measure, with a Bonferroni correction for multiple comparisons (α=.001). We focused on 2 primary outcomes that are indicative of asthma exacerbations: annual emergency department (ED) or inpatient visits for respiratory issues; and annual prescriptions for prednisone.

Results

Of the 157,410 patients within the asthma cohort, 26,332 (16.73%) had 1 or more annual ED or inpatient visits for respiratory issues, and 17,056 (10.84%) had 1 or more annual prescriptions for prednisone. We found that close proximity to a major roadway or highway, exposure to high levels of particulate matter ≤2.5 μm (PM_2.5) or ozone, female sex, Caucasian race, low residential density, lack of health insurance, and low household income were significantly associated with asthma exacerbations (P<.001). Asthma exacerbations did not vary by rural versus urban residence. Moreover, the results were largely consistent across outcome measures.

Conclusions

Our results demonstrate that the open-source ICEES can be used to replicate and extend published findings on factors that influence asthma exacerbations. As a disease-agnostic, open-source approach for integrating, exposing, and exploring patient-level clinical and environmental exposures data, we believe that ICEES will have broad adoption by other institutions and application in environmental health and other biomedical fields.

Defining clinical outcome pathways

Here, we propose a broad concept of 'Clinical Outcome Pathways' (COPs), which are defined as a series of key molecular and cellular events that underlie therapeutic effects of drug molecules. We formalize COPs as a chain of the following events: molecular initiating event (MIE) → intermediate event(s) → clinical outcome. We illustrate the concept with COP examples both for primary and alternative (i.e., drug repurposing) therapeutic applications. We also describe the elucidation of COPs for several drugs of interest using the publicly accessible Reasoning Over Biomedical Objects linked in Knowledge-Oriented Pathways (ROBOKOP) biomedical knowledge graph-mining tool. We propose that broader use of COP uncovered with the help of biomedical knowledge graph mining will likely accelerate drug discovery and repurposing efforts.

Open Application of Statistical and Machine Learning Models to Explore the Impact of Environmental Exposures on Health and Disease: An Asthma Use Case

ICEES (Integrated Clinical and Environmental Exposures Service) provides a disease-agnostic, regulatory-compliant approach for openly exposing and analyzing clinical data that have been integrated at the patient level with environmental exposures data. ICEES is equipped with basic features to support exploratory analysis using statistical approaches, such as bivariate chi-square tests. We recently developed a method for using ICEES to generate multivariate tables for subsequent application of machine learning and statistical models. The objective of the present study was to use this approach to identify predictors of asthma exacerbations through the application of three multivariate methods: conditional random forest, conditional tree, and generalized linear model. Among seven potential predictor variables, we found five to be of significant importance using both conditional random forest and conditional tree: prednisone, race, airborne particulate exposure, obesity, and sex. The conditional tree method additionally identified several significant two-way and three-way interactions among the same variables. When we applied a generalized linear model, we identified four significant predictor variables, namely prednisone, race, airborne particulate exposure, and obesity. When ranked in order by effect size, the results were in agreement with the results from the conditional random forest and conditional tree methods as well as the published literature. Our results suggest that the open multivariate analytic capabilities provided by ICEES are valid in the context of an asthma use case and likely will have broad value in advancing open research in environmental and public health.

Enabling Longitudinal Exploratory Analysis of Clinical COVID Data

As the COVID-19 pandemic continues to impact the world, data is being gathered and analyzed to better understand the disease. Recognizing the potential for visual analytics technologies to support exploratory analysis and hypothesis generation from longitudinal clinical data, a team of collaborators worked to apply existing event sequence visual analytics technologies to a longitudinal clinical data from a cohort of 998 patients with high rates of COVID-19 infection. This paper describes the initial steps toward this goal, including: (1) the data transformation and processing work required to prepare the data for visual analysis, (2) initial findings and observations, and (3) qualitative feedback and lessons learned which highlight key features as well as limitations to address in future work.

A Biomedical Knowledge Graph System to Propose Mechanistic Hypotheses for Real-World Environmental Health Observations: Cohort Study and Informatics Application

BACKGROUND

Knowledge graphs are a common form of knowledge representation in biomedicine and many other fields. We developed an open biomedical knowledge graph-based system termed Reasoning Over Biomedical Objects linked in Knowledge Oriented Pathways (ROBOKOP). ROBOKOP consists of both a front-end user interface and a back-end knowledge graph. The ROBOKOP user interface allows users to posit questions and explore answer subgraphs. Users can also posit questions through direct Cypher query of the underlying knowledge graph, which currently contains roughly 6 million nodes or biomedical entities and 140 million edges or predicates describing the relationship between nodes, drawn from over 30 curated data sources.

OBJECTIVE

We aimed to apply ROBOKOP to survey data on workplace exposures and immune-mediated diseases from the Environmental Polymorphisms Registry (EPR) within the National Institute of Environmental Health Sciences.

METHODS

We analyzed EPR survey data and identified 45 associations between workplace chemical exposures and immune-mediated diseases, as self-reported by study participants (n= 4574), with 20 associations significant at P<.05 after false discovery rate correction. We then used ROBOKOP to (1) validate the associations by determining whether plausible connections exist within the ROBOKOP knowledge graph and (2) propose biological mechanisms that might explain them and serve as hypotheses for subsequent testing. We highlight the following three exemplar associations: carbon monoxide-multiple sclerosis, ammonia-asthma, and isopropanol-allergic disease.

RESULTS

ROBOKOP successfully returned answer sets for three queries that were posed in the context of the driving examples. The answer sets included potential intermediary genes, as well as supporting evidence that might explain the observed associations.

CONCLUSIONS

We demonstrate real-world application of ROBOKOP to generate mechanistic hypotheses for associations between workplace chemical exposures and immune-mediated diseases. We expect that ROBOKOP will find broad application across many biomedical fields and other scientific disciplines due to its generalizability, speed to discovery and generation of mechanistic hypotheses, and open nature.

Application of MCAT questions as a testing tool and evaluation metric for knowledge graph-based reasoning systems

“Knowledge graphs” (KGs) have become a common approach for representing biomedical knowledge. In a KG, multiple biomedical data sets can be linked together as a graph representation, with nodes representing entities, such as “chemical substance” or “genes,” and edges representing predicates, such as “causes” or “treats.” Reasoning and inference algorithms can then be applied to the KG and used to generate new knowledge. We developed three KG‐based question‐answering systems as part of the Biomedical Data Translator program. These systems are typically tested and evaluated using traditional software engineering tools and approaches. In this study, we explored a team‐based approach to test and evaluate the prototype “Translator Reasoners” through the application of Medical College Admission Test (MCAT) questions. Specifically, we describe three “hackathons,” in which the developers of each of the three systems worked together with a moderator to determine whether the applications could be used to solve MCAT questions. The results demonstrate progressive improvement in system performance, with 0% (0/5) correct answers during the first hackathon, 75% (3/4) correct during the second hackathon, and 100% (5/5) correct during the final hackathon. We discuss the technical and sociologic lessons learned and conclude that MCAT questions can be applied successfully in the context of moderated hackathons to test and evaluate prototype KG‐based question‐answering systems, identify gaps in current capabilities, and improve performance. Finally, we highlight several published clinical and translational science applications of the Translator Reasoners.

A novel approach for exposing and sharing clinical data: the Translator Integrated Clinical and Environmental Exposures Service

OBJECTIVE

This study aimed to develop a novel, regulatory-compliant approach for openly exposing integrated clinical and environmental exposures data: the Integrated Clinical and Environmental Exposures Service (ICEES).

MATERIALS AND METHODS

The driving clinical use case for research and development of ICEES was asthma, which is a common disease influenced by hundreds of genes and a plethora of environmental exposures, including exposures to airborne pollutants. We developed a pipeline for integrating clinical data on patients with asthma-like conditions with data on environmental exposures derived from multiple public data sources. The data were integrated at the patient and visit level and used to create de-identified, binned, "integrated feature tables," which were then placed behind an OpenAPI.

RESULTS

Our preliminary evaluation results demonstrate a relationship between exposure to high levels of particulate matter ≤2.5 µm in diameter (PM2.5) and the frequency of emergency department or inpatient visits for respiratory issues. For example, 16.73% of patients with average daily exposure to PM2.5 >9.62 µg/m3 experienced 2 or more emergency department or inpatient visits for respiratory issues in year 2010 compared with 7.93% of patients with lower exposures (n = 23 093).

DISCUSSION

The results validated our overall approach for openly exposing and sharing integrated clinical and environmental exposures data. We plan to iteratively refine and expand ICEES by including additional years of data, feature variables, and disease cohorts.

CONCLUSIONS

We believe that ICEES will serve as a regulatory-compliant model and approach for promoting open access to and sharing of integrated clinical and environmental exposures data.

An approach for open multivariate analysis of integrated clinical and environmental exposures data

The Integrated Clinical and Environmental Exposures Service (ICEES) provides regulatory-compliant open access to sensitive patient data that have been integrated with public exposures data. ICEES was designed initially to support dynamic cohort creation and bivariate contingency tests. The objective of the present study was to develop an open approach to support multivariate analyses using existing ICEES functionalities and abiding by all regulatory constraints. We first developed an open approach for generating a multivariate table that maintains contingencies between clinical and environmental variables using programmatic calls to the open ICEES application programming interface. We then applied the approach to data on a large cohort (N = 22,365) of patients with asthma or related conditions and generated an eight-feature table. Due to regulatory constraints, data loss was incurred with the incorporation of each successive feature variable, from a starting sample size of N = 22,365 to a final sample size of N = 4,556 (20.4%), but data loss was < 10% until the addition of the final two feature variables. We then applied a generalized linear model to the subsequent dataset and focused on the impact of seven select feature variables on asthma exacerbations, defined as annual emergency department or inpatient visits for respiratory issues. We identified five feature variables—sex, race, obesity, prednisone, and airborne particulate exposure—as significant predictors of asthma exacerbations. We discuss the advantages and disadvantages of ICEES open multivariate analysis and conclude that, despite limitations, ICEES can provide a valuable resource for open multivariate analysis and can serve as an exemplar for regulatory-compliant informatic solutions to open patient data, with capabilities to explore the impact of environmental exposures on health outcomes.

Visualization Environment for Federated Knowledge Graphs: Development of an Interactive Biomedical Query Language and Web Application Interface

BACKGROUND

Efforts are underway to semantically integrate large biomedical knowledge graphs using common upper-level ontologies to federate graph-oriented application programming interfaces (APIs) to the data. However, federation poses several challenges, including query routing to appropriate knowledge sources, generation and evaluation of answer subsets, semantic merger of those answer subsets, and visualization and exploration of results.

OBJECTIVE

We aimed to develop an interactive environment for query, visualization, and deep exploration of federated knowledge graphs.

METHODS

We developed a biomedical query language and web application interphase-termed as Translator Query Language (TranQL)-to query semantically federated knowledge graphs and explore query results. TranQL uses the Biolink data model as an upper-level biomedical ontology and an API standard that has been adopted by the Biomedical Data Translator Consortium to specify a protocol for expressing a query as a graph of Biolink data elements compiled from statements in the TranQL query language. Queries are mapped to federated knowledge sources, and answers are merged into a knowledge graph, with mappings between the knowledge graph and specific elements of the query. The TranQL interactive web application includes a user interface to support user exploration of the federated knowledge graph.

RESULTS

We developed 2 real-world use cases to validate TranQL and address biomedical questions of relevance to translational science. The use cases posed questions that traversed 2 federated Translator API endpoints: Integrated Clinical and Environmental Exposures Service (ICEES) and Reasoning Over Biomedical Objects linked in Knowledge Oriented Pathways (ROBOKOP). ICEES provides open access to observational clinical and environmental data, and ROBOKOP provides access to linked biomedical entities, such as "gene," "chemical substance," and "disease," that are derived largely from curated public data sources. We successfully posed queries to TranQL that traversed these endpoints and retrieved answers that we visualized and evaluated.

CONCLUSIONS

TranQL can be used to ask questions of relevance to translational science, rapidly obtain answers that require assertions from a federation of knowledge sources, and provide valuable insights for translational research and clinical practice.

ROBOKOP: an abstraction layer and user interface for knowledge graphs to support question answering

SUMMARY

Knowledge graphs (KGs) are quickly becoming a common-place tool for storing relationships between entities from which higher-level reasoning can be conducted. KGs are typically stored in a graph-database format, and graph-database queries can be used to answer questions of interest that have been posed by users such as biomedical researchers. For simple queries, the inclusion of direct connections in the KG and the storage and analysis of query results are straightforward; however, for complex queries, these capabilities become exponentially more challenging with each increase in complexity of the query. For instance, one relatively complex query can yield a KG with hundreds of thousands of query results. Thus, the ability to efficiently query, store, rank and explore sub-graphs of a complex KG represents a major challenge to any effort designed to exploit the use of KGs for applications in biomedical research and other domains. We present Reasoning Over Biomedical Objects linked in Knowledge Oriented Pathways as an abstraction layer and user interface to more easily query KGs and store, rank and explore query results.

AVAILABILITY AND IMPLEMENTATION

An instance of the ROBOKOP UI for exploration of the ROBOKOP Knowledge Graph can be found at http://robokop.renci.org. The ROBOKOP Knowledge Graph can be accessed at http://robokopkg.renci.org. Code and instructions for building and deploying ROBOKOP are available under the MIT open software license from https://github.com/NCATS-Gamma/robokop.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

FHIR PIT: an open software application for spatiotemporal integration of clinical data and environmental exposures data

BACKGROUND

Informatics tools to support the integration and subsequent interrogation of spatiotemporal data such as clinical data and environmental exposures data are lacking. Such tools are needed to support research in environmental health and any biomedical field that is challenged by the need for integrated spatiotemporal data to examine individual-level determinants of health and disease.

RESULTS

We have developed an open-source software application-FHIR PIT (Health Level 7 Fast Healthcare Interoperability Resources Patient data Integration Tool)-to enable studies on the impact of individual-level environmental exposures on health and disease. FHIR PIT was motivated by the need to integrate patient data derived from our institution's clinical warehouse with a variety of public data sources on environmental exposures and then openly expose the data via ICEES (Integrated Clinical and Environmental Exposures Service). FHIR PIT consists of transformation steps or building blocks that can be chained together to form a transformation and integration workflow. Several transformation steps are generic and thus can be reused. As such, new types of data can be incorporated into the modular FHIR PIT pipeline by simply reusing generic steps or adding new ones. We validated FHIR PIT in the context of a driving use case designed to investigate the impact of airborne pollutant exposures on asthma. Specifically, we replicated published findings demonstrating racial disparities in the impact of airborne pollutants on asthma exacerbations.

CONCLUSIONS

While FHIR PIT was developed to support our driving use case on asthma, the software can be used to integrate any type and number of spatiotemporal data sources at a level of granularity that enables individual-level study. We expect FHIR PIT to facilitate research in environmental health and numerous other biomedical disciplines.

Sex, obesity, diabetes, and exposure to particulate matter among patients with severe asthma: Scientific insights from a comparative analysis of open clinical data sources during a five-day hackathon

This special communication describes activities, products, and lessons learned from a recent hackathon that was funded by the National Center for Advancing Translational Sciences via the Biomedical Data Translator program ('Translator'). Specifically, Translator team members self-organized and worked together to conceptualize and execute, over a five-day period, a multi-institutional clinical research study that aimed to examine, using open clinical data sources, relationships between sex, obesity, diabetes, and exposure to airborne fine particulate matter among patients with severe asthma. The goal was to develop a proof of concept that this new model of collaboration and data sharing could effectively produce meaningful scientific results and generate new scientific hypotheses. Three Translator Clinical Knowledge Sources, each of which provides open access (via Application Programming Interfaces) to data derived from the electronic health record systems of major academic institutions, served as the source of study data. Jupyter Python notebooks, shared in GitHub repositories, were used to call the knowledge sources and analyze and integrate the results. The results replicated established or suspected relationships between sex, obesity, diabetes, exposure to airborne fine particulate matter, and severe asthma. In addition, the results demonstrated specific differences across the three Translator Clinical Knowledge Sources, suggesting cohort- and/or environment-specific factors related to the services themselves or the catchment area from which each service derives patient data. Collectively, this special communication demonstrates the power and utility of intense, team-oriented hackathons and offers general technical, organizational, and scientific lessons learned.

Fast Healthcare Interoperability Resources (FHIR) as a Meta Model to Integrate Common Data Models: Development of a Tool and Quantitative Validation Study

Background

In a multisite clinical research collaboration, institutions may or may not use the same common data model (CDM) to store clinical data. To overcome this challenge, we proposed to use Health Level 7’s Fast Healthcare Interoperability Resources (FHIR) as a meta-CDM—a single standard to represent clinical data.

Objective

In this study, we aimed to create an open-source application termed the Clinical Asset Mapping Program for FHIR (CAMP FHIR) to efficiently transform clinical data to FHIR for supporting source-agnostic CDM-to-FHIR mapping.

Methods

Mapping with CAMP FHIR involves (1) mapping each source variable to its corresponding FHIR element and (2) mapping each item in the source data’s value sets to the corresponding FHIR value set item for variables with strict value sets. To date, CAMP FHIR has been used to transform 108 variables from the Informatics for Integrating Biology & the Bedside (i2b2) and Patient-Centered Outcomes Research Network data models to fields across 7 FHIR resources. It is designed to allow input from any source data model and will support additional FHIR resources in the future.

Results

We have used CAMP FHIR to transform data on approximately 23,000 patients with asthma from our institution’s i2b2 database. Data quality and integrity were validated against the origin point of the data, our enterprise clinical data warehouse.

Conclusions

We believe that CAMP FHIR can serve as an alternative to implementing new CDMs on a project-by-project basis. Moreover, the use of FHIR as a CDM could support rare data sharing opportunities, such as collaborations between academic medical centers and community hospitals. We anticipate adoption and use of CAMP FHIR to foster sharing of clinical data across institutions for downstream applications in translational research.

Semantic integration of clinical laboratory tests from electronic health records for deep phenotyping and biomarker discovery

Electronic Health Record (EHR) systems typically define laboratory test results using the Laboratory Observation Identifier Names and Codes (LOINC) and can transmit them using Fast Healthcare Interoperability Resource (FHIR) standards. LOINC has not yet been semantically integrated with computational resources for phenotype analysis. Here, we provide a method for mapping LOINC-encoded laboratory test results transmitted in FHIR standards to Human Phenotype Ontology (HPO) terms. We annotated the medical implications of 2923 commonly used laboratory tests with HPO terms. Using these annotations, our software assesses laboratory test results and converts each result into an HPO term. We validated our approach with EHR data from 15,681 patients with respiratory complaints and identified known biomarkers for asthma. Finally, we provide a freely available SMART on FHIR application that can be used within EHR systems. Our approach allows readily available laboratory tests in EHR to be reused for deep phenotyping and exploits the hierarchical structure of HPO to integrate distinct tests that have comparable medical interpretations for association studies.

Scientific Training in the Era of Big Data: A New Pedagogy for Graduate Education

The era of "big data" has radically altered the way scientific research is conducted and new knowledge is discovered. Indeed, the scientific method is rapidly being complemented and even replaced in some fields by data-driven approaches to knowledge discovery. This paradigm shift is sometimes referred to as the "fourth paradigm" of data-intensive and data-enabled scientific discovery. Interdisciplinary research with a hard emphasis on translational outcomes is becoming the norm in all large-scale scientific endeavors. Yet, graduate education remains largely focused on individual achievement within a single scientific domain, with little training in team-based, interdisciplinary data-oriented approaches designed to translate scientific data into new solutions to today's critical challenges. In this article, we propose a new pedagogy for graduate education: data-centered learning for the domain-data scientist. Our approach is based on four tenets: (1) Graduate training must incorporate interdisciplinary training that couples the domain sciences with data science. (2) Graduate training must prepare students for work in data-enabled research teams. (3) Graduate training must include education in teaming and leadership skills for the data scientist. (4) Graduate training must provide experiential training through academic/industry practicums and internships. We emphasize that this approach is distinct from today's graduate training, which offers training in either data science or a domain science (e.g., biology, sociology, political science, economics, and medicine), but does not integrate the two within a single curriculum designed to prepare the next generation of domain-data scientists. We are in the process of implementing the proposed pedagogy through the development of a new graduate curriculum based on the above four tenets, and we describe herein our strategy, progress, and lessons learned. While our pedagogy was developed in the context of graduate education, the general approach of data-centered learning can and should be applied to students and professionals at any stage of their education, including at the K-12, undergraduate, graduate, and professional levels. We believe that the time is right to embed data-centered learning within our educational system and, thus, generate the talent required to fully harness the potential of big data.

A New Framework and Prototype Solution for Clinical Decision Support and Research in Genomics and Other Data-intensive Fields of Medicine

Introduction:

In genomics and other fields, it is now possible to capture and store large amounts of data in electronic medical records (EMRs). However, it is not clear if the routine accumulation of massive amounts of (largely uninterpretable) data will yield any health benefits to patients. Nevertheless, the use of large-scale medical data is likely to grow. To meet emerging challenges and facilitate optimal use of genomic data, our institution initiated a comprehensive planning process that addresses the needs of all stakeholders (e.g., patients, families, healthcare providers, researchers, technical staff, administrators). Our experience with this process and a key genomics research project contributed to the proposed framework.

Framework:

We propose a two-pronged Genomic Clinical Decision Support System (CDSS) that encompasses the concept of the “Clinical Mendeliome” as a patient-centric list of genomic variants that are clinically actionable and introduces the concept of the “Archival Value Criterion” as a decision-making formalism that approximates the cost-effectiveness of capturing, storing, and curating genome-scale sequencing data. We describe a prototype Genomic CDSS that we developed as a first step toward implementation of the framework.

Conclusion:

The proposed framework and prototype solution are designed to address the perspectives of stakeholders, stimulate effective clinical use of genomic data, drive genomic research, and meet current and future needs. The framework also can be broadly applied to additional fields, including other ‘-omics’ fields. We advocate for the creation of a Task Force on the Clinical Mendeliome, charged with defining Clinical Mendeliomes and drafting clinical guidelines for their use.

Postoperative mortality after inpatient surgery: Incidence and risk factors

Purpose:

This study determined the incidence of and identified risk factors for 48 hour (h) and 30 day (d) postoperative mortality after inpatient operations.

Methods:

A retrospective cohort study was conducted using Anesthesiology’s Quality Indicator database as the main data source. The database was queried for data related to the surgical procedure, anesthetic care, perioperative adverse events, and birth/death/operation dates. The 48 h and 30 d cumulative incidence of postoperative mortality was calculated and data were analyzed using Chi-square or Fisher’s exact test and generalized estimating equations.

Results:

The 48 h and 30 d incidence of postoperative mortality was 0.57% and 2.1%, respectively. Higher American Society of Anesthesiologists physical status scores, extremes of age, emergencies, perioperative adverse events and postoperative Intensive Care Unit admission were identified as risk factors. The use of monitored anesthesia care or general anesthesia versus regional or combined anesthesia was a risk factor for 30 d postoperative mortality only. Time under anesthesia care, perioperative hypothermia, trauma, deliberate hypotension and invasive monitoring via arterial, pulmonary artery or cardiovascular catheters were not identified as risk factors.

Conclusions:

Our findings can be used to track postoperative mortality rates and to test preventative interventions at our institution and elsewhere.

Continuous epidural infusion of morphine versus single epidural injection of extended-release morphine for postoperative pain control after arthroplasty: a retrospective analysis

BACKGROUND

This study retrospectively compared the continuous epidural infusion of morphine with a single epidural injection of extended-release morphine for postoperative pain control after arthroplasty.

METHODS

Medical records were reviewed for subjects who had total knee or hip arthroplasty (THA) under spinal anesthesia and received either a continuous epidural infusion of morphine (Group EPID; n = 101) or an extended-release epidural morphine (Group EREM; n = 109) for postoperative pain. Data were collected for three postoperative days (POD) on: pain scores; supplemental opioids; medications for respiratory depression, nausea, and pruritus, and distance ambulated during physical therapy.

RESULTS

Pain scores were similar until subjects were transitioned to another analgesic approach on POD 2; after that time, pain scores increased in Group EPID, although they decreased in Group EREM. Supplemental opioids were used more on POD1 in Group EREM than in Group EPID, although time to first opioid and total daily morphine equivalents were similar. Naloxone and antiemetics, not antipruritics, were used more in Group EREM. Distance ambulated after THA was greater in Group EREM than in Group EPID.

CONCLUSIONS

These results suggest that EREM is associated with better postoperative ambulation and analgesia during the transition to oral or intravenous analgesics, although a higher incidence of side-effects was evident.

Vocal cord function and bispectral index in pediatric bronchoscopy patients emerging from propofol anesthesia

OBJECTIVE

In children undergoing bronchoscopy for evaluation of stridor or respiratory symptoms, movement of the vocal cords is routinely assessed at the conclusion of flexible bronchoscopy with children still anesthetized. The effect of anesthesia on vocal cord function is not well described. This study aimed to characterize the relationship between depth of propofol anesthesia, as measured by Bispectral Index (BIS), and vocal cord movement in pediatric patients.

METHODS

Children between 6 months and 12 years of age presenting for diagnostic flexible bronchoscopy were enrolled in this prospective observational study. Anesthesia was maintained with a propofol infusion which was discontinued upon completion of the lower airway evaluation. An independent observer recorded the BIS score every 15 sec from discontinuation of propofol whereas the pulmonologist continued to observe vocal cord motion. BIS scores were also recorded for each observed clinical endpoint (paradoxical and normal vocal cord movement, complete vocal cord closure, and volitional movement).

RESULTS

Data were analyzed for 47 subjects. The BIS values increased significantly from the conclusion of the lower airway evaluation with return of normal vocal cord movement, complete vocal cord closure, and volitional movement (P < 0.0005). BIS readings were higher for patients younger than 2 years. Paradoxical vocal cord movement was documented in 10.6% of subjects, but resolved in all subjects.

CONCLUSIONS

Our findings suggest that return of vocal cord function during emergence from propofol anesthesia is related to decreasing anesthetic depth with complete vocal cord closure occurring at BIS values near those associated with volitional movement.

In-hospital resuscitation: opioids and other factors influencing survival

PURPOSE

"Code Blue" is a standard term used to alertt hospital staff that a patient requires resuscitation. This study determined rates of survival from Code Blue events and the role of opioids and other factors on survival.

METHODS

Data derived from medical records and the Code Blue and Pharmacy databases were analyzed for factors affecting survival.

RESULTS

During 2006, rates of survival from the code only and to discharge were 25.9% and 26.4%, respectively, for Code Blue events involving cardiopulmonary resuscitation (CPR; N = 216). Survival rates for events not ultimately requiring CPR (N = 77) were higher, with 32.5% surviving the code only and 62.3% surviving to discharge. For CPR events, rates of survival to discharge correlated inversely with time to chest compressions and defibrillation, precipitating event, need for airway management, location and age. Time of week, witnessing, postoperative status, gender and opioid use did not influence survival rates. For non-CPR events, opioid use was associated with decreased survival. Survival rates were lowest for patients receiving continuous infusions (P < 0.01) or iv boluses of opioids (P < 0.05).

CONCLUSIONS

One-quarter of patients survive to discharge after a CPR Code Blue event and two-thirds survive to discharge after a non-CPR event. Opioids may influence survival from non-CPR events.

Anesthesia-related perioperative adverse events during in-patient and out-patient procedures

PURPOSE

This paper aims to determine the one-year incidence of, and risk factors for, perioperative adverse events during in-patient and out-patient anesthesia-assisted procedures.

DESIGN/METHODOLOGY/APPROACH

A quality assurance database was the primary data source. Outcome variables were death and the occurrence of any adverse event. Risk factors were ASA physical status (PS), age, duration and type of anesthesia care, number of operating rooms running, concurrency level and medical staff. Data were stratified by in-patient or out-patient, surgical (e.g. thoracotomy) or non-surgical (e.g. electroconvulsive therapy), and were analyzed using Chi square, Fisher's exact test and generalized estimating equations.

FINDINGS

Of 27,970 procedures, 49.8 percent were out-patient and greater than 80 percent were surgical. For surgical procedures, adverse event rates were higher for in-patient than out-patient procedures (2.11 percent vs. 1.45 percent; p < 0.001). For non-surgical procedures, adverse event rates were similar for in-patients and out-patients (0.54 percent vs. 0.36 percent). The types of adverseevents differed for in-patient and out-patient surgical procedures (p < 0.001), but not for non-surgical procedures. ASA PS, age, duration of anesthesia care, anesthesia type and medical staff assigned to the case were each associated with adverse event rates, but the association depended on the type of procedure.

PRACTICAL IMPLICATIONS

In-patient and out-patient surgical procedures differ in the incidence of perioperative adverse events, and in risk factors, suggesting a need to develop separate monitoring strategies.

ORIGINALITY/VALUE

The paper is the first to assess perioperative adverse events amongst in-patient and out-patient procedures.

Effects of carrageenan and morphine on acute inflammation and pain in Lewis and Fischer rats

The present study used inbred, histocompatible Fischer 344 (FIS) and Lewis (LEW) rats to begin to explore the role of the hypothalamic-pituitary-adrenal (HPA) axis in the immune processes and pain behavior associated with the carrageenan model of acute hindpaw inflammation. Because the HPA axis contributes in part to morphine's analgesic and immunomodulatory properties, the present study also assessed the effects of morphine in carrageenan-inflamed LEW and FIS rats. The results showed that carrageenan-induced hindpaw swelling and pain behavior were greater in FIS than in LEW rats. The enhanced hindpaw swelling in FIS rats correlated with an increase in myeloperoxidase (MPO; a measure of neutrophils) in the inflamed hindpaw. FIS rats showed lower circulating levels of TNFalpha, higher IL-6 levels, and similar IL-1beta and nitric oxide levels, when compared to LEW rats. Morphine produced a significant decrease in carrageenan-induced hindpaw swelling and MPO in both strains, but morphine did not significantly alter circulating cytokine/mediator levels. Morphine's analgesic effects were greater in the inflamed than the noninflamed hindpaw, and they did not correlate with morphine's anti-inflammatory effects. In fact, low doses of morphine produced a mechanical allodynia and hyperalgesia in the noninflamed hindpaw of FIS, but not LEW, rats. These results suggest a positive relationship between HPA axis activity and acute inflammation and inflammatory pain. In contrast, little evidence is provided for HPA axis involvement in morphine's anti-inflammatory or analgesic effects.

Catechol-O-methyltransferase inhibition increases pain sensitivity through activation of both beta2- and beta3-adrenergic receptors

Catechol-O-methyltransferase (COMT), an enzyme that metabolizes catecholamines, has recently been implicated in the modulation of pain. Our group demonstrated that human genetic variants of COMT are predictive for the development of Temporomandibular Joint Disorder (TMJD) and are associated with heightened experimental pain sensitivity [Diatchenko, L, Slade, GD, Nackley, AG, Bhalang, K, Sigurdsson, A, Belfer, I, et al., Genetic basis for individual variations in pain perception and the development of a chronic pain condition, Hum Mol Genet 2005;14:135-43.]. Variants associated with heightened pain sensitivity produce lower COMT activity. Here we report the mechanisms underlying COMT-dependent pain sensitivity. To characterize the means whereby elevated catecholamine levels, resulting from reduced COMT activity, modulate heightened pain sensitivity, we administered a COMT inhibitor to rats and measured behavioral responsiveness to mechanical and thermal stimuli. We show that depressed COMT activity results in enhanced mechanical and thermal pain sensitivity. This phenomenon is completely blocked by the nonselective beta-adrenergic antagonist propranolol or by the combined administration of selective beta(2)- and beta(3)-adrenergic antagonists, while administration of beta(1)-adrenergic, alpha-adrenergic, or dopaminergic receptor antagonists fail to alter COMT-dependent pain sensitivity. These data provide the first direct evidence that low COMT activity leads to increased pain sensitivity via a beta(2/3)-adrenergic mechanism. These findings are of considerable clinical importance, suggesting that pain conditions resulting from low COMT activity and/or elevated catecholamine levels can be treated with pharmacological agents that block both beta(2)- and beta(3)-adrenergic receptors.

Acute inflammatory and neuropathic pain in Lewis and Fischer rats

Inbred, histocompatible Lewis and Fischer 344 rats (LEW and FIS) have been used to identify an inverse relationship between hypothalamic-pituitary-adrenal (HPA) axis activity and susceptibility to autoimmune and chronic inflammatory disorders, with LEW showing blunted HPA axis activity and increased susceptibility toward the development of autoimmunity and chronic inflammation, and FIS showing the opposite relationship. In the present study, LEW and FIS were used to determine the relationship between HPA axis function and acute inflammatory pain (carrageenan-induced hindpaw inflammation) and neuropathic pain (partial sciatic nerve ligation; PSNL). The results showed that carrageenan-induced thermal and mechanical allodynia and hyperalgesia were greater in FIS than in LEW. Similarly, FIS showed more carrageenan-induced hindpaw swelling and higher levels of myeloperoxidase (a measure of neutrophils) in the carrageenan-inflamed hindpaw. After PSNL, LEW showed a profound mechanical allodynia and hyperalgesia, whereas mechanical sensitivity in FIS was unaltered. However, FIS, but not LEW, developed thermal allodynia and hyperalgesia after PSNL. These results provide strong evidence for a positive relationship between HPA axis activity and acute inflammatory pain. The results also support a relationship between HPA axis activity and neuropathic pain, but the relationship is complex and may depend on the pain assay.

Basal and carrageenan-induced pain behavior in Sprague-Dawley, Lewis and Fischer rats

Individual differences in pain sensitivity are believed to reflect the interplay of many factors, including genetics. Inbred rat strains can be used to study the impact of genetic factors on pain sensitivity. Inbred Lewis (LEW) and Fischer 344 (FIS) rat strains display profound and contrasting alterations in neuroendocrine, immunological and behavioral responses to stressors. Because of the established interactions between stressors, the neuroendocrine system, the immune system and pain processing pathways, we hypothesized that LEW and FIS rats would differ in their pain sensitivity. Pain sensitivity was assessed using several behavioral pain assays in untreated and carrageenan-inflamed LEW and FIS rats, and in the outbred Sprague-Dawley (SD) rat. The results showed that at baseline, FIS rats were the most sensitive to mechanical stimulation (the von Frey monofilament test) and the least sensitive to noxious heat pain (the Hargreaves radiant heat test). After intraplantar administration of carrageenan, LEW rats showed the least, and FIS rats showed the greatest, thermal hyperalgesia and mechanical allodynia/hyperalgesia. Hindlimb muscle grip force and tail-flick latencies did not differ across the three strains, either before or after carrageenan. These results demonstrate differences in basal and carrageenan-induced pain sensitivity in LEW, FIS and SD rats, which extend earlier findings that genetic factors modulate both basal and inflammatory pain. The results further demonstrate that basal pain sensitivity can be predictive of inflammatory pain sensitivity, with the direction of the effect dependent upon the pain measure.

Morphine-induced enhancement in the granulocyte response to thioglycollate administration in the rat

The present study determined the pharmacological effects of acute morphine treatment on the granulocyte phase of the peritoneal inflammatory response to thioglycollate (TG) in rats. Dual-color flow cytometry using anti-CD11b/c-PE mAb in combination with HIS48-FITC mAb allowed for the determination of morphine's effects on 4 inflammatory cell subsets: CD11b/c(+)HIS48med granulocytes; CD11b/c(hi)HIS48neg/lo activated macrophages; CD11b/c(-)HIS48(-) lymphocytes; and CD11b/c(+)HIS48hi cells (a monocyte/macrophage and granulocyte subset). Morphine produced a dose-dependent increase in a select subset of inflammatory peritoneal cells, the CD11b/c(+)HIS48med granulocytes. The effect of morphine was time-dependent, with significant effects first apparent at 4 hr after TG, but the administration of morphine 1 hr before or simultaneously with TG produced a similar increase in CD11b/c(+)HIS48med granulocytes. Naltrexone completely antagonized the morphine-induced increase in CD11b/c(+)HIS48med granulocytes. Collectively, these studies show that a single administration of morphine produces a time-dependent, dose-dependent, opioid receptor-mediated enhancement in the peritoneal granulocyte response to TG.

Heroin-induced alterations in leukocyte numbers and apoptosis in the rat spleen

The present study assessed the effects of acute heroin treatment on the cellularity of the rat spleen and the rate of splenocyte death by necrosis or apoptosis. The results showed that 1 h after a single injection of heroin, the total number of leukocytes in the spleen was decreased in a dose-dependent manner. Prior injection of naltrexone completely blocked heroin's effect, and the heroin-induced decrease in splenic leukocytes was not associated with a heroin-induced increase in circulating leukocytes. A 1-h exposure to heroin did not increase levels of lactate dehydrogenase, a cytosolic enzyme, in supernatants of splenic mononuclear cells cultured for 45 min or 24 h, suggesting that heroin does not increase necrotic death in the spleen. In contrast, a 1-h heroin treatment did increase the percentage of Annexin V(+) cells in 0- and 24-h cultures of splenic mononuclear cells, indicating that heroin increases apoptotic death in the spleen. A 3-h exposure to heroin also produced a significant increase in apoptosis in the spleen. DNA fragmentation, a marker of cells in late stages of apoptosis, could not be detected in fresh splenocytes, but was evident in 24-h cultures of splenic mononuclear cells from saline- and heroin-treated rats. These results demonstrate that a single administration of heroin produces a decrease in the number of splenic leukocytes and an increase in the apoptotic death of splenic mononuclear cells.

Phenotypic and functional assessments of immune status in the rat spleen following acute heroin treatment

Heroin use is associated with an increased incidence of several types of infections, including HIV. Yet few studies have assessed whether heroin produces pharmacological alterations of immune status that might contribute to the increased rate of infections amongst heroin users. The present study investigated whether a single administration of heroin to rats produces dose-dependent alterations in functional measures of immune status and in the distribution of leukocyte subsets in the spleen. The results showed that heroin produces a dose-dependent, naltrexone-reversible suppression of the concanavalin A-stimulated proliferation of T cells, lipopolysaccharide-stimulated proliferation of B cells, production of interferon-gamma and cytotoxicity of natural killer (NK) cells in the spleen. Heroin's suppressive effect on NK cell activity results in part from a heroin-induced decrease in the relative number of NKR-P1A(hi) CD3- NK cells in the spleen. Heroin also decreases the percent of a splenic granulocyte subset, the CD11b/c+ HIS48(hi) cells, whose function currently is unknown. In contrast, heroin does not alter relative numbers of CD4+ CD3+ T cells, CD8+ CD3+ T cells, CD45+ B cells, NKR-P1A(lo) CD3+ T cells, CD11b/c+ ED1+ (or CD11b/c+ HIS48-) monocytes/macrophages or CD11b/c+ ED1- (or CD11b/c+ HIS48+) total granulocytes in the spleen. Collectively, these findings demonstrate that heroin produces pharmacological effects on functional and phenotypic measures of immune status.

Differential Control of Autoantibodies and Lymphoproliferation by Fas Ligand Expression on CD4+ and CD8+ T Cells In Vivo

We have previously shown that the gld autoimmune syndrome is suppressed in lethally irradiated gld mice reconstituted with a mixture of normal and gld bone marrow (BM). Furthermore, in vivo depletion of normal Thy-1+ cells restores lymphoproliferation and autoantibody production in such chimeras, suggesting that T cells bearing Fas ligand are responsible for correcting the gld defect. In this study, mixed-BM chimeras lacking either normal CD4+ (B6CD4KO-B6gld) or normal CD8+ T cells (B6CD8KO-B6gld) were generated to determine the contribution of the normal T cell subsets to disease suppression. Lymphoproliferation was completely suppressed in B6CD4KO-B6gld chimeras but only modestly in B6CD8KO-B6gld chimeras. On the other hand, both types of mixed-BM chimeras had incomplete effects on the suppression of serum autoantibodies when compared with B6gld reconstituted with isologous BM. These results suggest that both T cell subsets provide Fas ligand to suppress immune cells responsible for autoantibody production; however, CD8+ T cells are mainly responsible for preventing lymphoproliferation.

Differential control of autoantibodies and lymphoproliferation by Fas ligand expression on CD4+ and CD8+ T cells in vivo

We have previously shown that the gld autoimmune syndrome is suppressed in lethally irradiated gld mice reconstituted with a mixture of normal and gld bone marrow (BM). Furthermore, in vivo depletion of normal Thy-1+ cells restores lymphoproliferation and autoantibody production in such chimeras, suggesting that T cells bearing Fas ligand are responsible for correcting the gld defect. In this study, mixed-BM chimeras lacking either normal CD4+ (B6CD4KO-B6gld) or normal CD8+ T cells (B6CD8KO-B6gld) were generated to determine the contribution of the normal T cell subsets to disease suppression. Lymphoproliferation was completely suppressed in B6CD4KO-B6gld chimeras but only modestly in B6CD8KO-B6gld chimeras. On the other hand, both types of mixed-BM chimeras had incomplete effects on the suppression of serum autoantibodies when compared with B6gld reconstituted with isologous BM. These results suggest that both T cell subsets provide Fas ligand to suppress immune cells responsible for autoantibody production; however, CD8+ T cells are mainly responsible for preventing lymphoproliferation.

Phenotypic analysis of splenocyte subsets following acute morphine treatment in the rat

Prior studies by our laboratory demonstrated that a single injection of morphine produces dose-dependent, naltrexone-reversible, suppressive effects in assays of mitogen-stimulated lymphocyte proliferation and natural killer (NK) cell cytotoxicity in the spleen. The present study used flow cytometry to assess directly whether acute morphine treatment produces these immune alterations by altering the leukocyte composition of the spleen. In agreement with our previous findings, morphine suppressed the concanavalin A-stimulated proliferation of T cells, lipopolysaccharide-stimulated proliferation of B cells, and NK cell cytotoxicity in the spleen. However, the same morphine treatment protocol did not alter the total number of splenic leukocytes, the percentage of live splenic leukocytes (as assessed by forward-scatter versus side-scatter histograms), or the relative number of CD4(+)CD3(+) T cells, CD8(+)CD3(+) T cells, CD45RA/B(+) B cells, NKR-P1A(hi)CD3(-) NK cells, NKR-P1A(lo)CD3(+) T cells, CD11b/c(+)HIS48(-) monocytes/macrophages, or CD11b/c(+)HIS48(+) granulocytes in the spleen. These findings indicate that the effects of a single sc dose of morphine on functional measures of immune status in the spleen do not result from a redistribution of splenic leukocytes; instead, morphine's effects likely result from direct alterations in leukocyte activities.

Fas ligand (gld)- and Fas (lpr)-deficient mice do not show alterations in the extravasation or apoptosis of inflammatory neutrophils

Apoptosis of neutrophils plays a critical role in the resolution of acute inflammation. Neutrophils from human peripheral blood express Fas (CD95) and are sensitive to Fas ligand (FasL)/Fas-mediated apoptosis. Mice carrying spontaneous mutations in the genes for fas ligand (B6/gld) or fas (B6/lpr) were used to assess the role of FasL/Fas in the kinetics and magnitude of neutrophil extravasation to the thioglycolate (TG)-inflamed peritoneum and in the spontaneous apoptosis of TG-elicited neutrophils. The results showed that TG-elicited neutrophils (defined by flow cytometry as GR-1/Ly-6G(hi) cells) from normal (B6) and B6/gld mice, but not from the Fas-deficient B6/lpr mice, express high levels of Fas. The TG-elicited neutrophil response began at 2 h, peaked at 4 h, and subsided by 24-48 h after TG administration in all three strains. However, the response was more prolonged in B6 mice, such that B6/gld and B6/lpr mice had fewer neutrophils at 6 h after TG administration than did B6 mice. Further studies showed that 4 h TG-elicited neutrophils from B6, B6/gld and B6/lpr mice undergo apoptosis in vitro at similar rates (as assessed through flow cytometry by the decrease in forward angle light-scatter and externalization of phosphatidylserine (PS; as detected by Annexin V-FITC) that occur as neutrophils undergo apoptosis). Fas expression was down-regulated on apoptotic neutrophils in conjunction with maximal PS externalization and decreased forward angle light-scatter. Collectively, these findings suggest that FasL/Fas-mediated apoptosis is not essential in regulating the lifespan of neutrophils during an acute inflammatory response. The abbreviated inflammatory response observed in FasL/Fas-deficient mice is likely to be a secondary effect of the gld/lpr autoimmune/lymphoproliferative syndrome, and not a direct effect of FasL/Fas on the ability of inflammatory neutrophils to undergo apoptosis.

Mice deficient in fas ligand (gld) or fas (lpr) show few alterations in granulopoiesis

Evidence exists that the life span of mature, circulating neutrophils is influenced by apoptosis induced by interactions between Fas ligand (FasL) and Fas (CD95). However, the role of FasL/Fas-mediated apoptosis in granulopoiesis has not been explored. The present study assessed differences in granulopoiesis between normal (B6) mice and mice carrying mutations in the genes for FasL (B6/gld) or Fas (B6/lpr). Granulopoiesis was examined by quantitating mature granulocytes in the blood, committed myeloid progenitor cells (or colony-forming units; CFU) in the bone marrow (BM), and granulocyte lineage cells in the BM. The present study also characterized through flow cytometry the ability of GR-1(+) granulocyte lineage cells from B6, B6/gld, and B6/lpr mice to undergo spontaneous apoptosis in vitro. In comparison to B6 mice, B6/gld mice (but not B6/lpr mice) showed small, but significant increases in the number and percentage of blood granulocytes and in the number of myeloid CFU. However, the number and percentage of GR-1(+) granulocyte lineage cells in the BM were similar in the three strains. The rate of spontaneous apoptosis of GR-1(+) granulocyte lineage cells also did not differ between B6, B6/gld, and B6/lpr mice. In B6 and B6/gld mice, Fas expression on granulocyte lineage cells was downregulated in conjunction with a decrease in forward-angle light scatter (fsc) and externalization of phosphatidylserine (PS), two measures of apoptosis. These results suggest that FasL-Fas interactions play only a minor role in modulating numbers of committed myeloid progenitor cells and the size of the peripheral pool of mature granulocytes. Interactions between FasL and Fas do not influence the size of the BM pool of granulocyte lineage cells or the ability of those cells to undergo spontaneous apoptosis.

Acetylcholinesterase monoclonal antibody-induced sympathectomy: effects on immune status and acute morphine-induced immunomodulation

The present study examined the role of the sympathetic nervous system (SNS) in immunomodulation by using the acetylcholinesterase monoclonal antibody (AChE mAb)-induced sympathectomy model. As part of this investigation, the effects of AChE mAb treatment on the immune alterations produced by acute morphine treatment also were explored. Experimental rats received tail vein injections of murine monoclonal IgG2b antibodies against rat brain acetylcholinesterase, which produce a destruction of cholinergic, sympathetic preganglionic neurons and a resultant decrease in sympathetic activity. Control rats received tail vein injections of murine IgG antibodies, which do not affect sympathetic preganglionic neurons or sympathetic activity. One week after antibody treatment, rats received a subcutaneous injection of 15 mg/kg morphine or the saline vehicle. One hour after the morphine or saline injections, rats were sacrificed and immune assays were conducted. AChE mAb treatment increased the mitogen-stimulated proliferation of splenic T cells and interleukin-2 (IL-2) production by stimulated splenocytes, indicating that these immune measures are sensitive to the AChE mAb-induced alteration in sympathetic function. Treatment with AChE mAb did not alter the mitogen-stimulated proliferation of splenic B cells or blood T cells, splenic natural killer (NK) cell activity, or the production of interferon-gamma (IFN-gamma) by stimulated splenocytes, indicating that these immune measures are relatively insensitive to the AChE mAb-induced alteration in sympathetic activity. The AChE mAb-induced alteration in sympathetic activity did not affect the suppressive effects of acute morphine treatment on the mitogen-stimulated proliferative response of splenic T and B cells and blood T cells, splenic NK cell activity, and the production of IFN-gamma and IL-2 by stimulated splenocytes.

Evidence for sympathetic and adrenal involvement in the immunomodulatory effects of acute morphine treatment in rats

The present study examined the involvement of the sympathetic nervous system and the hypothalamic-pituitary-adrenal axis in the immunomodulatory effects of acute morphine treatment in rats. Chlorisondamine, a ganglionic blocker, was used to assess the involvement of sympathetic and sympathoadrenal activity. Adrenalectomized rats were used to assess the involvement of the adrenal cortex, which is regulated primarily by hypothalamic-pituitary-adrenal axis activity, and the adrenal medulla, which is regulated primarily by sympathetic activity. The results showed that both chlorisondamine and adrenalectomy antagonize morphine's suppressive effects on the proliferative response of splenic lymphocytes to concanavalin A (Con A), lipopolysaccharide or ionomycin/phorbol myristate acetate. Chlorisondamine, but not adrenalectomy, antagonizes morphine's suppressive effects on phytohemagglutinin (PHA)-stimulated proliferation of splenic lymphocytes and interferon-gamma production by stimulated splenocytes. Adrenalectomy, but not chlorisondamine, blocks morphine's suppressive effects on the proliferative response of blood lymphocytes to Con A or PHA. Neither chlorisondamine nor adrenalectomy alters morphine's suppressive effect on splenic natural killer cell cytotoxicity. Collectively, these results suggest that sympathoadrenal activity is involved in the suppressive effects of acute morphine treatment on the proliferative response of splenic T and B cells to Con A, lipopolysaccharide or ionomycin/phorbol myristate acetate. Morphine's suppressive effects on the proliferative response of splenic T cells to PHA and the production of interferon-gamma by stimulated splenocytes also involve sympathetic activity, but not sympathoadrenal activity. The results suggest further that morphine's suppressive effects on the proliferative response of blood T cells to Con A or PHA do not involve sympathetic activity, but rather adrenocortical activity. Neither sympathetic nor adrenocortical activity appears to be involved in morphine's suppressive effect on splenic natural killer cell cytotoxicity.

Assessment of the involvement of central nervous system and peripheral opioid receptors in the immunomodulatory effects of acute morphine treatment in rats

The present study assessed the involvement of opioid receptors both in the central nervous system (CNS) and in the periphery (i.e., on immunocytes) in the immune alterations produced by acute morphine treatment in rats. The first experiment showed that the in vitro suppressive effects of morphine on the mitogen-stimulated proliferation of splenic and blood lymphocytes are produced only by a very high concentration of morphine and are not naltrexone-reversible. These results suggest that the in vitro immunomodulatory effects of morphine are not mediated by classical opioid receptors on immunocytes. A second experiment showed that s.c. doses of N-methylnaltrexone that do not gain access to the CNS, as determined by the tail-withdrawal assay, do not antagonize the suppressive effects of a single, s.c. injection of morphine on the mitogen-stimulated proliferation of splenic and blood lymphocytes, splenic natural killer cell activity and the production of interferon-gamma by stimulated splenocytes. Only a high s.c. dose of N-methylnaltrexone that does gain access to the CNS, as determined by the tail-withdrawal assay, blocks morphine's immunomodulatory effects. A third experiment demonstrated that N-methylnaltrexone is 4 to 5 log units more potent in antagonizing most of the immune alterations produced by a single, s.c. injection of morphine when administered i.c.v. than s.c. Taken together, the results of the present study strongly suggest that CNS opioid receptors play an important role in the immune alterations produced by acute morphine treatment in rats.

Mechanisms whereby macrophage-derived nitric oxide is involved in morphine-induced suppression of splenic lymphocyte proliferation

Previous research by our laboratory demonstrated that in vivo administration of morphine to rats suppresses concanavalin-A (Con-A)-stimulated proliferation of splenic lymphocytes in a dose-dependent, naltrexone-reversible manner. More recently, we showed that morphine-induced suppression of Con A-stimulated proliferation of lymphocytes depends on an increase in macrophage production of nitric oxide (NO) in splenocyte cultures. The present study investigated effector mechanisms through which morphine-induced increases in macrophage-derived NO decrease lymphocyte proliferation in Con A-stimulated splenocyte cultures. The results show that the addition of hemoglobin, a scavenger of extracellular NO, to Con A-stimulated splenocyte cultures dose-dependently attenuates the suppressive effect of morphine on proliferation. The addition of superoxide dismutase, a scavenger of superoxide anions, to splenocyte cultures does not antagonize the suppressive effect of morphine on Con A-stimulated proliferation. The addition of either methylene blue or 6-anilino-5, 8-quinolinedione (LY 83583), two inhibitors of soluble guanylate cyclase, to splenocyte cultures dose-dependently antagonizes the suppressive effect of morphine on Con A-stimulated proliferation. Taken together with our previous results, the present results suggest that in vivo administration of morphine increases the synthesis and extracellular release of NO from macrophages in Con A-stimulated splenocyte cultures. The results further suggest that the formation of the oxidant peroxynitrite through a reaction between NO and superoxide anion does not contribute significantly to the suppression of lymphocyte proliferation; instead, the activation of soluble guanylate cyclase by NO in target cells, most likely the lymphocytes, accounts more completely for the morphine-induced suppression of lymphocyte proliferation.