Translate text to:
In JoVE (1)
Other Publications (17)
- American Journal of Veterinary Research
- BMC Genetics
- The Journal of Experimental Biology
- PLoS Computational Biology
- Journal of the American Medical Informatics Association : JAMIA
- Ecology and Evolution
- PloS One
- AMIA ... Annual Symposium Proceedings. AMIA Symposium
- Journal of the American Medical Informatics Association : JAMIA
- BMC Medical Genomics
- Studies in Health Technology and Informatics
- Studies in Health Technology and Informatics
- BMC Medical Genomics
- Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
- Database : the Journal of Biological Databases and Curation
- The Journal of Surgical Research
- OncoTargets and Therapy
Articles by Kelly Regan in JoVE
Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System
Kelly Regan1, Soheil Moosavinasab2, Philip Payne1, Simon Lin2
1Department of Biomedical Informatics, The Ohio State University, 2Research Information Solutions and Innovation, The Research Institute at Nationwide Children’s Hospital
Other articles by Kelly Regan on PubMed
American Journal of Veterinary Research. Feb, 2008 | Pubmed ID: 18241019
To characterize heritability and mode of inheritance of cataracts and primary lens luxation in Jack Russell Terriers.
BMC Genetics. May, 2010 | Pubmed ID: 20441595
Idiopathic epilepsy in the Belgian shepherd dog is known to have a substantial genetic component. The objective of this study was to identify genomic regions associated with the expression of generalized seizures in the Belgian Tervuren and Sheepdog.
Neuroepithelial Cells and the Hypoxia Emersion Response in the Amphibious Fish Kryptolebias Marmoratus
The Journal of Experimental Biology. Aug, 2011 | Pubmed ID: 21753050
Teleost fish have oxygen-sensitive neuroepithelial cells (NECs) in the gills that appear to mediate physiological responses to hypoxia, but little is known about oxygen sensing in amphibious fish. The mangrove rivulus, Kryptolebias marmoratus, is an amphibious fish that respires via the gills and/or the skin. First, we hypothesized that both the skin and gills are sites of oxygen sensing in K. marmoratus. Serotonin-positive NECs were abundant in both gills and skin, as determined by immunohistochemical labelling and fluorescence microscopy. NECs retained synaptic vesicles and were found near nerve fibres labelled with the neuronal marker zn-12. Skin NECs were 42% larger than those of the gill, as estimated by measurement of projection area, and 45% greater in number. Moreover, for both skin and gill NECs, NEC area increased significantly (30-60%) following 7 days of exposure to hypoxia (1.5 mg l(-1) dissolved oxygen). Another population of cells containing vesicular acetylcholine transporter (VAChT) proteins were also observed in the skin and gills. The second hypothesis we tested was that K. marmoratus emerse in order to breathe air cutaneously when challenged with severe aquatic hypoxia, and this response will be modulated by neurochemicals associated chemoreceptor activity. Acute exposure to hypoxia induced fish to emerse at 0.2 mg l(-1). When K. marmoratus were pre-exposed to serotonin or acetylcholine, they emersed at a significantly higher concentration of oxygen than untreated fish. Pre-exposure to receptor antagonists (ketanserin and hexamethonium) predictably resulted in fish emersing at a lower concentration of oxygen. Taken together, these results suggest that oxygen sensing occurs at the branchial and/or cutaneous surfaces in K. marmoratus and that serotonin and acetylcholine mediate, in part, the emersion response.
PLoS Computational Biology. Jan, 2012 | Pubmed ID: 22291585
Gene expression signatures that are predictive of therapeutic response or prognosis are increasingly useful in clinical care; however, mechanistic (and intuitive) interpretation of expression arrays remains an unmet challenge. Additionally, there is surprisingly little gene overlap among distinct clinically validated expression signatures. These "causality challenges" hinder the adoption of signatures as compared to functionally well-characterized single gene biomarkers. To increase the utility of multi-gene signatures in survival studies, we developed a novel approach to generate "personal mechanism signatures" of molecular pathways and functions from gene expression arrays. FAIME, the Functional Analysis of Individual Microarray Expression, computes mechanism scores using rank-weighted gene expression of an individual sample. By comparing head and neck squamous cell carcinoma (HNSCC) samples with non-tumor control tissues, the precision and recall of deregulated FAIME-derived mechanisms of pathways and molecular functions are comparable to those produced by conventional cohort-wide methods (e.g. GSEA). The overlap of "Oncogenic FAIME Features of HNSCC" (statistically significant and differentially regulated FAIME-derived genesets representing GO functions or KEGG pathways derived from HNSCC tissue) among three distinct HNSCC datasets (pathways:46%, p<0.001) is more significant than the gene overlap (genes:4%). These Oncogenic FAIME Features of HNSCC can accurately discriminate tumors from control tissues in two additional HNSCC datasets (nâ€Š=â€Š35 and 91, F-accuracyâ€Š=â€Š100% and 97%, empirical p<0.001, area under the receiver operating characteristic curvesâ€Š=â€Š99% and 92%), and stratify recurrence-free survival in patients from two independent studies (pâ€Š=â€Š0.0018 and pâ€Š=â€Š0.032, log-rank). Previous approaches depending on group assignment of individual samples before selecting features or learning a classifier are limited by design to discrete-class prediction. In contrast, FAIME calculates mechanism profiles for individual patients without requiring group assignment in validation sets. FAIME is more amenable for clinical deployment since it translates the gene-level measurements of each given sample into pathways and molecular function profiles that can be applied to analyze continuous phenotypes in clinical outcome studies (e.g. survival time, tumor volume).
Translating Mendelian and Complex Inheritance of Alzheimer's Disease Genes for Predicting Unique Personal Genome Variants
Journal of the American Medical Informatics Association : JAMIA. Mar, 2012 | Pubmed ID: 22319180
Objective Although trait-associated genes identified as complex versus single-gene inheritance differ substantially in odds ratio, the authors nonetheless posit that their mechanistic concordance can reveal fundamental properties of the genetic architecture, allowing the automated interpretation of unique polymorphisms within a personal genome. Materials and methods An analytical method, SPADE-gen, spanning three biological scales was developed to demonstrate the mechanistic concordance between Mendelian and complex inheritance of Alzheimer's disease (AD) genes: biological functions (BP), protein interaction modeling, and protein domain implicated in the disease-associated polymorphism. Results Among Gene Ontology (GO) biological processes (BP) enriched at a false detection rate <5% in 15 AD genes of Mendelian inheritance (Online Mendelian Inheritance in Man) and independently in those of complex inheritance (25 host genes of intragenic AD single-nucleotide polymorphisms confirmed in genome-wide association studies), 16 overlapped (empirical p=0.007) and 45 were similar (empirical p<0.009; information theory). SPAN network modeling extended the canonical pathway of AD (KEGG) with 26 new protein interactions (empirical p<0.0001). Discussion The study prioritized new AD-associated biological mechanisms and focused the analysis on previously unreported interactions associated with the biological processes of polymorphisms that affect specific protein domains within characterized AD genes and their direct interactors using (1) concordant GO-BP and (2) domain interactions within STRING protein-protein interactions corresponding to the genomic location of the AD polymorphism (eg, EPHA1, APOE, and CD2AP). Conclusion These results are in line with unique-event polymorphism theory, indicating how disease-associated polymorphisms of Mendelian or complex inheritance relate genetically to those observed as 'unique personal variants'. They also provide insight for identifying novel targets, for repositioning drugs, and for personal therapeutics.
Environmental Diel Variation, Parasite Loads, and Local Population Structuring of a Mixed-mating Mangrove Fish
Ecology and Evolution. Jul, 2012 | Pubmed ID: 22957172
Genetic variation within populations depends on population size, spatial structuring, and environmental variation, but is also influenced by mating system. Mangroves are some of the most productive and threatened ecosystems on earth and harbor a large proportion of species with mixed-mating (self-fertilization and outcrossing). Understanding population structuring in mixed-mating species is critical for conserving and managing these complex ecosystems. Kryptolebias marmoratus is a unique mixed-mating vertebrate inhabiting mangrove swamps under highly variable tidal regimes and environmental conditions. We hypothesized that geographical isolation and ecological pressures influence outcrossing rates and genetic diversity, and ultimately determine the local population structuring of K. marmoratus. By comparing genetic variation at 32 microsatellites, diel fluctuations of environmental parameters, and parasite loads among four locations with different degrees of isolation, we found significant differences in genetic diversity and genotypic composition but little evidence of isolation by distance. Locations also differed in environmental diel fluctuation and parasite composition. Our results suggest that mating system, influenced by environmental instability and parasites, underpins local population structuring of K. marmoratus. More generally, we discuss how the conservation of selfing species inhabiting mangroves and other biodiversity hotspots may benefit from knowledge of mating strategies and population structuring at small spatial scales.
Oligo- and Polymetastatic Progression in Lung Metastasis(es) Patients is Associated with Specific MicroRNAs
PloS One. 2012 | Pubmed ID: 23251360
Strategies to stage and treat cancer rely on a presumption of either localized or widespread metastatic disease. An intermediate state of metastasis termed oligometastasis(es) characterized by limited progression has been proposed. Oligometastases are amenable to treatment by surgical resection or radiotherapy.
Towards Mechanism Classifiers: Expression-anchored Gene Ontology Signature Predicts Clinical Outcome in Lung Adenocarcinoma Patients
AMIA ... Annual Symposium Proceedings. AMIA Symposium. 2012 | Pubmed ID: 23304380
We aim to provide clinically applicable, reproducible, mechanistic interpretations of gene expression changes that lack in gene overlap among predictive gene-signatures. Using a method we recently developed, Functional Analysis of Individual Microarray Expression (FAIME), we provide evidence that Gene Ontology-anchored signatures (GO-signatures) show reliable prognosis in lung cancer. In order to demonstrate the biological congruence and reproducibility of FAIME-derived mechanism classifiers, we chose a disease where gene expression classifiers signatures alone had failed to significantly stratify a larger collection of samples and that exhibited poor or no genetic overlap. For each patient in the two lung adenocarcinoma studies, personalized FAIME-profiles of GO biological processes are generated from genome-wide expression profiles. For both training studies, GO-signatures significantly associated to patient mortality were identified (Prediction Analysis for Microarrays; three-fold cross-validation). These two GO-signatures could effectively stratify patients from an independent validation cohort into sub-groups that show significant differences in disease-free survival (log-rank test P=0.019; P=0.001). Importantly, significant mechanism overlaps assessed by information-theory similarity were detected between the two GO-signatures (Fischer Exact Test p=0.001). Hence, together with machine learning technologies, FAIME could be utilized to develop an ontology-driven and expression-anchored prognostic signature that is personalized for an individual patient.
Network Models of Genome-wide Association Studies Uncover the Topological Centrality of Protein Interactions in Complex Diseases
Journal of the American Medical Informatics Association : JAMIA. Jul-Aug, 2013 | Pubmed ID: 23355459
While genome-wide association studies (GWAS) of complex traits have revealed thousands of reproducible genetic associations to date, these loci collectively confer very little of the heritability of their respective diseases and, in general, have contributed little to our understanding the underlying disease biology. Physical protein interactions have been utilized to increase our understanding of human Mendelian disease loci but have yet to be fully exploited for complex traits.
In Silico Cancer Cell Versus Stroma Cellularity Index Computed from Species-specific Human and Mouse Transcriptome of Xenograft Models: Towards Accurate Stroma Targeting Therapy Assessment
BMC Medical Genomics. 2014 | Pubmed ID: 25079962
The current state of the art for measuring stromal response to targeted therapy requires burdensome and rate limiting quantitative histology. Transcriptome measures are increasingly affordable and provide an opportunity for developing a stromal versus cancer ratio in xenograft models. In these models, human cancer cells are transplanted into mouse host tissues (stroma) and together coevolve into a tumour microenvironment. However, profiling the mouse or human component separately remains problematic. Indeed, laser capture microdissection is labour intensive. Moreover, gene expression using commercial microarrays introduces significant and underreported cross-species hybridization errors that are commonly overlooked by biologists.
Studies in Health Technology and Informatics. 2015 | Pubmed ID: 26262083
Liver cancer, the fifth most common cancer and second leading cause of cancer-related death among men worldwide, is plagued by not only lack of clinical research, but informatics tools for early detection. Consequently, it presents a major health and cost burden. Among the different types of liver cancer, hepatocellular carcinoma (HCC) is the most common and deadly form, arising from underlying liver disease. Current models for predicting risk of HCC and liver disease are limited to clinical data. A domain analysis of existing research related to screening for HCC and liver disease suggests that metabolic syndrome (MetS) may present oppportunites to detect early signs of liver disease. The purpose of this paper is to (i) provide a domain analysis of the relationship between HCC, liver disease, and metabolic syndrome, (ii) a review of the current disparate sources of data available for MetS diagnosis, and (iii) recommend informatics solutions for the diagnosis of MetS from available administrative (Biometrics, PHA, claims) and laboratory data, towards early prediction of liver disease. Our domain analysis and recommendations incorporate best practices to make meaningful use of available data with the goal of reducing cost associated with liver disease.
Studies in Health Technology and Informatics. 2015 | Pubmed ID: 26262134
The worldwide incidence of melanoma is rising faster than any other cancer, and prognosis for patients with metastatic disease is poor. Current targeted therapies are limited in their durability and/or effect size in certain patient populations due to acquired mechanisms of resistance. Thus, the development of synergistic combinatorial treatment regimens holds great promise to improve patient outcomes. We have previously shown that a model for in-silico knowledge discovery, Translational Ontology-anchored Knowledge Discovery Engine (TOKEn), is able to generate valid relationships between bimolecular and clinical phenotypes. In this study, we have aggregated observational and canonical knowledge consisting of melanoma-related biomolecular entities and targeted therapeutics in a computationally tractable model. We demonstrate here that the explicit linkage of therapeutic modalities with biomolecular underpinnings of melanoma utilizing the TOKEn pipeline yield a set of informed relationships that have the potential to generate combination therapy strategies.
Gene Expression Profiling of the Human Natural Killer Cell Response to Fc Receptor Activation: Unique Enhancement in the Presence of Interleukin-12
BMC Medical Genomics. Oct, 2015 | Pubmed ID: 26470881
Traditionally, the CD56(dim)CD16(+) subset of Natural Killer (NK) cells has been thought to mediate cellular cytotoxicity with modest cytokine secretion capacity. However, studies have suggested that this subset may exert a more diverse array of immunological functions. There exists a lack of well-developed functional models to describe the behavior of activated NK cells, and the interactions between signaling pathways that facilitate effector functions are not well understood. In the present study, a combination of genome-wide microarray analyses and systems-level bioinformatics approaches were utilized to elucidate the transcriptional landscape of NK cells activated via interactions with antibody-coated targets in the presence of interleukin-12 (IL-12).
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing. 2016 | Pubmed ID: 26776168
Database : the Journal of Biological Databases and Curation. 2016 | Pubmed ID: 27189611
The process of discovering new drugs has been extremely costly and slow in the last decades despite enormous investment in pharmaceutical research. Drug repurposing enables researchers to speed up the process of discovering other conditions that existing drugs can effectively treat, with low cost and fast FDA approval. Here, we introduce 'RE:fine Drugs', a freely available interactive website for integrated search and discovery of drug repurposing candidates from GWAS and PheWAS repurposing datasets constructed using previously reported methods in Nature Biotechnology. 'RE:fine Drugs' demonstrates the possibilities to identify and prioritize novelty of candidates for drug repurposing based on the theory of transitive Drug-Gene-Disease triads. This public website provides a starting point for research, industry, clinical and regulatory communities to accelerate the investigation and validation of new therapeutic use of old drugs.Database URL: http://drug-repurposing.nationwidechildrens.org.
The Journal of Surgical Research. Oct, 2016 | Pubmed ID: 27664883
Melanoma skin cancer remains the leading cause of skin cancer-related deaths. Spitz lesions represent a subset of melanocytic skin lesions characterized by epithelioid or spindled melanocytes organized in nests. These lesions occupy a spectrum ranging from benign Spitz and atypical Spitz lesions all the way to malignant Spitz tumors. Appropriate management is reliant on accurate diagnostic classification, yet this effort remains challenging using current light microscopic techniques. The discovery of novel biomarkers such as microRNAs (miR) may ultimately be a useful diagnostic adjunct for the evaluation of Spitz lesions. miR expression profiles have been suggested for non-Spitz melanomas but have yet to be ascribed to Spitz lesions. We hypothesized that distinct miR expression profiles would be associated with different lesions along the Spitz spectrum.
MicroRNA Profiling of Patient Plasma for Clinical Trials Using Bioinformatics and Biostatistical Approaches
OncoTargets and Therapy. 2016 | Pubmed ID: 27729802
MicroRNAs (miRNAs) are short noncoding RNAs that function to repress translation of mRNA transcripts and contribute to the development of cancer. We hypothesized that miRNA array-based technologies work best for miRNA profiling of patient-derived plasma samples when the techniques and patient populations are precisely defined.