Mouse phenome database: curated data repository with interactive multi-population and multi-trait analyses.

The Mouse Phenome Database continues to serve as a curated repository and analysis suite for measured attributes of members of diverse mouse populations. The repository includes annotation to community standard ontologies and guidelines, a database of allelic states for 657 mouse strains, a collection of protocols, and analysis tools for flexible, interactive, user directed analyses that increasingly integrates data across traits and populations. The database has grown from its initial focus on a standard set of inbred strains to include heterogeneous mouse populations such as the Diversity Outbred and mapping crosses and well as Collaborative Cross, Hybrid Mouse Diversity Panel, and recombinant inbred strains. Most recently the system has expanded to include data from the International Mouse Phenotyping Consortium. Collectively these data are accessible by API and provided with an interactive tool suite that enables users' persistent selection, storage, and operation on collections of measures. The tool suite allows basic analyses, advanced functions with dynamic visualization including multi-population meta-analysis, multivariate outlier detection, trait pattern matching, correlation analyses and other functions. The data resources and analysis suite provide users a flexible environment in which to explore the basis of phenotypic variation in health and disease across the lifespan.

Mouse Phenome Database: a data repository and analysis suite for curated primary mouse phenotype data.

The Mouse Phenome Database (MPD; https://phenome.jax.org) is a widely accessed and highly functional data repository housing primary phenotype data for the laboratory mouse accessible via APIs and providing tools to analyze and visualize those data. Data come from investigators around the world and represent a broad scope of phenotyping endpoints and disease-related traits in naïve mice and those exposed to drugs, environmental agents or other treatments. MPD houses rigorously curated per-animal data with detailed protocols. Public ontologies and controlled vocabularies are used for annotation. In addition to phenotype tools, genetic analysis tools enable users to integrate and interpret genome-phenome relations across the database. Strain types and populations include inbred, recombinant inbred, F1 hybrid, transgenic, targeted mutants, chromosome substitution, Collaborative Cross, Diversity Outbred and other mapping populations. Our new analysis tools allow users to apply selected data in an integrated fashion to address problems in trait associations, reproducibility, polygenic syndrome model selection and multi-trait modeling. As we refine these tools and approaches, we will continue to provide users a means to identify consistent, quality studies that have high translational relevance.

Mouse Phenome Database: an integrative database and analysis suite for curated empirical phenotype data from laboratory mice.

The Mouse Phenome Database (MPD; https://phenome.jax.org) is a widely used resource that provides access to primary experimental trait data, genotypic variation, protocols and analysis tools for mouse genetic studies. Data are contributed by investigators worldwide and represent a broad scope of phenotyping endpoints and disease-related traits in naïve mice and those exposed to drugs, environmental agents or other treatments. MPD houses individual animal data with detailed, searchable protocols, and makes these data available to other resources via API. MPD provides rigorous curation of experimental data and supporting documentation using relevant ontologies and controlled vocabularies. Most data in MPD are from inbreds and other reproducible strains such that the data are cumulative over time and across laboratories. The resource has been expanded to include the QTL Archive and other primary phenotype data from mapping crosses as well as advanced high-diversity mouse populations including the Collaborative Cross and Diversity Outbred mice. Furthermore, MPD provides a means of assessing replicability and reproducibility across experimental conditions and protocols, benchmarking assays in users' own laboratories, identifying sensitized backgrounds for making new mouse models with genome editing technologies, analyzing trait co-inheritance, finding the common genetic basis for multiple traits and assessing sex differences and sex-by-genotype interactions.

Mouse phenome database.

The Mouse Phenome Database (MPD; phenome.jax.org) was launched in 2001 as the data coordination center for the international Mouse Phenome Project. MPD integrates quantitative phenotype, gene expression and genotype data into a common annotated framework to facilitate query and analysis. MPD contains >3500 phenotype measurements or traits relevant to human health, including cancer, aging, cardiovascular disorders, obesity, infectious disease susceptibility, blood disorders, neurosensory disorders, drug addiction and toxicity. Since our 2012 NAR report, we have added >70 new data sets, including data from Collaborative Cross lines and Diversity Outbred mice. During this time we have completely revamped our homepage, improved search and navigational aspects of the MPD application, developed several web-enabled data analysis and visualization tools, annotated phenotype data to public ontologies, developed an ontology browser and released new single nucleotide polymorphism query functionality with much higher density coverage than before. Here, we summarize recent data acquisitions and describe our latest improvements.

Mouse Phenome Database (MPD).

The Mouse Phenome Project was launched a decade ago to complement mouse genome sequencing efforts by promoting new phenotyping initiatives under standardized conditions and collecting the data in a central public database, the Mouse Phenome Database (MPD; http://phenome.jax.org). MPD houses a wealth of strain characteristics data to facilitate the use of the laboratory mouse in translational research for human health and disease, helping alleviate problems involving experimentation in humans that cannot be done practically or ethically. Data sets are voluntarily contributed by researchers from a variety of institutions and settings, or in some cases, retrieved by MPD staff from public sources. MPD maintains a growing collection of standardized reference data that assists investigators in selecting mouse strains for research applications; houses treatment/control data for drug studies and other interventions; offers a standardized platform for discovering genotype-phenotype relationships; and provides tools for hypothesis testing. MPD improvements and updates since our last NAR report are presented, including the addition of new tools and features to facilitate navigation and data mining as well as the acquisition of new data (phenotypic, genotypic and gene expression).

A Genomically and Clinically Annotated Patient-Derived Xenograft Resource for Preclinical Research in Non-Small Cell Lung Cancer.

Patient-derived xenograft (PDX) models are an effective preclinical in vivo platform for testing the efficacy of novel drugs and drug combinations for cancer therapeutics. Here we describe a repository of 79 genomically and clinically annotated lung cancer PDXs available from The Jackson Laboratory that have been extensively characterized for histopathologic features, mutational profiles, gene expression, and copy-number aberrations. Most of the PDXs are models of non-small cell lung cancer (NSCLC), including 37 lung adenocarcinoma (LUAD) and 33 lung squamous cell carcinoma (LUSC) models. Other lung cancer models in the repository include four small cell carcinomas, two large cell neuroendocrine carcinomas, two adenosquamous carcinomas, and one pleomorphic carcinoma. Models with both de novo and acquired resistance to targeted therapies with tyrosine kinase inhibitors are available in the collection. The genomic profiles of the LUAD and LUSC PDX models are consistent with those observed in patient tumors from The Cancer Genome Atlas and previously characterized gene expression-based molecular subtypes. Clinically relevant mutations identified in the original patient tumors were confirmed in engrafted PDX tumors. Treatment studies performed in a subset of the models recapitulated the responses expected on the basis of the observed genomic profiles. These models therefore serve as a valuable preclinical platform for translational cancer research. SIGNIFICANCE: Patient-derived xenografts of lung cancer retain key features observed in the originating patient tumors and show expected responses to treatment with standard-of-care agents, providing experimentally tractable and reproducible models for preclinical investigations.

Mouse phenome database.

The Mouse Phenome Database (MPD; http://www.jax.org/phenome) is an open source, web-based repository of phenotypic and genotypic data on commonly used and genetically diverse inbred strains of mice and their derivatives. MPD is also a facility for query, analysis and in silico hypothesis testing. Currently MPD contains about 1400 phenotypic measurements contributed by research teams worldwide, including phenotypes relevant to human health such as cancer susceptibility, aging, obesity, susceptibility to infectious diseases, atherosclerosis, blood disorders and neurosensory disorders. Electronic access to centralized strain data enables investigators to select optimal strains for many systems-based research applications, including physiological studies, drug and toxicology testing, modeling disease processes and complex trait analysis. The ability to select strains for specific research applications by accessing existing phenotype data can bypass the need to (re)characterize strains, precluding major investments of time and resources. This functionality, in turn, accelerates research and leverages existing community resources. Since our last NAR reporting in 2007, MPD has added more community-contributed data covering more phenotypic domains and implemented several new tools and features, including a new interactive Tool Demo available through the MPD homepage (quick link: http://phenome.jax.org/phenome/trytools).

Incidental pheochromocytoma: fifteen-year experience at a community hospital.

BACKGROUND: Pheochromocytoma is a well-recognized neuroendocrine tumor. Classical symptoms are well described, but recent studies have suggested that many patients are diagnosed incidentally. No studies have evaluated incidental pheochromocytoma with respect to year of diagnosis. METHODS: A retrospective study was performed from January 1992-November 2006 to evaluate the frequency of incidental pheochromocytoma. Patients were included if pathological specimens were available. RESULTS: 21 patients were included. 15/21 (71.4%) cases were incidentally discovered. 11/15 (73.3%) were diagnosed after 2000, while 4/15 (26.7%) were diagnosed before 2000. 15/21 (71.4%) patients had hypertension, and all 6 patients without hypertension had pheochromocytoma diagnosed incidentally. Only 3/21 (14.3%) patients were diagnosed by biochemical testing. DISCUSSION: This observational study suggests an increasing number of incidental pheochromocytomas. Several possibilities for this observation include increased usage of imaging studies, decreased use of biochemical testing, and an increase in referring patients to surgeons for resection without an appropriate endocrine work-up. Referring physicians and surgeons alike should take note of this.

Genetic Differences in Dorsal Hippocampus Acetylcholinesterase Activity Predict Contextual Fear Learning Across Inbred Mouse Strains.

Learning is a critical behavioral process that is influenced by many neurobiological systems. We and others have reported that acetylcholinergic signaling plays a vital role in learning capabilities, and it is especially important for contextual fear learning. Since cholinergic signaling is affected by genetic background, we examined the genetic relationship between activity levels of acetylcholinesterase (AChE), the primary enzyme involved in the acetylcholine metabolism, and learning using a panel of 20 inbred mouse strains. We measured conditioned fear behavior and AChE activity in the dorsal hippocampus, ventral hippocampus, and cerebellum. Acetylcholinesterase activity varied among inbred mouse strains in all three brain regions, and there were significant inter-strain differences in contextual and cued fear conditioning. There was an inverse correlation between fear conditioning outcomes and AChE levels in the dorsal hippocampus. In contrast, the ventral hippocampus and cerebellum AChE levels were not correlated with fear conditioning outcomes. These findings strengthen the link between acetylcholine activity in the dorsal hippocampus and learning, and they also support the premise that the dorsal hippocampus and ventral hippocampus are functionally discrete.

Mouse Phenome Database (MPD).

The Mouse Phenome Database (MPD; http://www.jax.org/phenome) is a repository of phenotypic and genotypic data on commonly used and genetically diverse inbred strains of mice. Strain characteristics data are contributed by members of the scientific community. Electronic access to centralized strain data enables biomedical researchers to choose appropriate strains for many systems-based research applications, including physiological studies, drug and toxicology testing and modeling disease processes. MPD provides a community data repository and a platform for data analysis and in silico hypothesis testing. The laboratory mouse is a premier genetic model for understanding human biology and pathology; MPD facilitates research that uses the mouse to identify and determine the function of genes participating in normal and disease pathways.

Pheochromocytoma: an easily overlooked cause of secondary hypertension.

Pheochromocytoma is a rare cause of secondary hypertension. Presentation varies from asymptomatic to paroxysmal hypertension, palpitations, flushing, syncope, and even shock or death. Diagnosis is often delayed because pheochromocytoma is not considered a likely diagnosis. We present the case of a 47-year-old male that presented with hypertensive emergency. Several diagnostic tests were performed prior to consideration of pheochromocytoma as the potential cause. Abdominal computed tomography revealed a nonspecific mass. A subsequent hormonal workup led to the diagnosis of pheochromocytoma. The patient underwent adrenalectomy seventeen days after presentation and postoperatively did well. This case demonstrates a typical presentation of pheochromocytoma and the need to consider pheochromocytoma early in the differential diagnosis of hypertensive emergency or difficult to control hypertension.

Genomic data analysis workflows for tumors from patient-derived xenografts (PDXs): challenges and guidelines.

BACKGROUND: Patient-derived xenograft (PDX) models are in vivo models of human cancer that have been used for translational cancer research and therapy selection for individual patients. The Jackson Laboratory (JAX) PDX resource comprises 455 models originating from 34 different primary sites (as of 05/08/2019). The models undergo rigorous quality control and are genomically characterized to identify somatic mutations, copy number alterations, and transcriptional profiles. Bioinformatics workflows for analyzing genomic data obtained from human tumors engrafted in a mouse host (i.e., Patient-Derived Xenografts; PDXs) must address challenges such as discriminating between mouse and human sequence reads and accurately identifying somatic mutations and copy number alterations when paired non-tumor DNA from the patient is not available for comparison. RESULTS: We report here data analysis workflows and guidelines that address these challenges and achieve reliable identification of somatic mutations, copy number alterations, and transcriptomic profiles of tumors from PDX models that lack genomic data from paired non-tumor tissue for comparison. Our workflows incorporate commonly used software and public databases but are tailored to address the specific challenges of PDX genomics data analysis through parameter tuning and customized data filters and result in improved accuracy for the detection of somatic alterations in PDX models. We also report a gene expression-based classifier that can identify EBV-transformed tumors. We validated our analytical approaches using data simulations and demonstrated the overall concordance of the genomic properties of xenograft tumors with data from primary human tumors in The Cancer Genome Atlas (TCGA). CONCLUSIONS: The analysis workflows that we have developed to accurately predict somatic profiles of tumors from PDX models that lack normal tissue for comparison enable the identification of the key oncogenic genomic and expression signatures to support model selection and/or biomarker development in therapeutic studies. A reference implementation of our analysis recommendations is available at https://github.com/TheJacksonLaboratory/PDX-Analysis-Workflows .

Accessing Data Resources in the Mouse Phenome Database for Genetic Analysis of Murine Life Span and Health Span.

Understanding the source of genetic variation in aging and using this variation to define the molecular mechanisms of healthy aging require deep and broad quantification of a host of physiological, morphological, and behavioral endpoints. The murine model is a powerful system in which to understand the relations across age-related phenotypes and to identify research models with variation in life span and health span. The Jackson Laboratory Nathan Shock Center of Excellence in the Basic Biology of Aging has performed broad characterization of aging in genetically diverse laboratory mice and has placed these data, along with data from several other major aging initiatives, into the interactive Mouse Phenome Database. The data may be accessed and analyzed by researchers interested in finding mouse models for specific aging processes, age-related health and disease states, and for genetic analysis of aging variation and trait covariation. We expect that by placing these data in the hands of the aging community that there will be (a) accelerated genetic analyses of aging processes, (b) discovery of genetic loci regulating life span, (c) identification of compelling correlations between life span and susceptibility for age-related disorders, and (d) discovery of concordant genomic loci influencing life span and aging phenotypes between mouse and humans.

"Where obesity goes, so goes diabetes"--dual epidemics of alarming proportions.

Diabetes and obesity are increasing in alarming, epidemic proportions not only in West Virginia, but also in the United States and in the world. Their combined toll encompasses not only an increased risk of premature cardiovascular disease and death, but multiple other associated co-morbidities. Recognition of their impact on healthcare systems is crucial and involves awareness and action on the part of providers at every level. Education is of paramount importance in combating these growing trends with preservation of the health and well-being of the populace as an ultimate goal.

The Mouse Phenome Project.

The laboratory mouse is the organism of choice for many studies in biology and medicine. Reliable phenotypic data are essential for the full utility of genotypic information emerging from efforts to sequence human and mouse genomes. The Mouse Phenome Project has been organized to help accomplish this task by establishing a collection of baseline phenotypic data on commonly used and genetically diverse inbred mouse strains and making this information publicly available through a web-accessible database. The Mouse Phenome Database (MPD) is being developed to manage these data and to provide researchers with tools for exploring both raw phenotypic data and comparative summary analyses. The MPD serves as a repository for detailed protocols and raw data. This resource enables investigators to identify appropriate strains for (1) physiological testing, (2) drug discovery, (3) toxicology studies, (4) mutagenesis, (5) modeling human diseases, (6) QTL analyses and identification of new genes and (7) unraveling the influence of environment on genotype.

A collaborative database of inbred mouse strain characteristics.

UNLABELLED: A database and website (MPD: Mouse Phenome Database) have been developed to serve as a consolidated home for mouse strain characterization data being generated by the scientific community. Physiological, anatomical and behavioral data are being collected and integrated into a common framework for tabulation by strain and sex. Genotypic data are being collected as well. The current focus is on a set of 40 inbred strains. The MPD as of February 2004 contains approximately 500 phenotypic parameters relevant to human health, voluntarily contributed by several dozen investigators and laboratories. AVAILABILITY: www.jax.org/phenome