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Article ; Online: Repurposing N-acetylcysteine for management of non-acetaminophen induced acute liver failure: an evidence scan from a global health perspective.

Jerome, Rebecca N / Zahn, Laura A / Abner, Jessica J / Joly, Meghan M / Shirey-Rice, Jana K / Wallis, Robert S / Bernard, Gordon R / Pulley, Jill M

Translational gastroenterology and hepatology

2024 Volume 9, Page(s) 2

Abstract: Background: The World Health Organization (WHO)'s Essential Medicines List (EML) plays an important role in advocating for access to key treatments for conditions affecting people in all geographic settings. We applied our established drug repurposing ... ...

Abstract	Background: The World Health Organization (WHO)'s Essential Medicines List (EML) plays an important role in advocating for access to key treatments for conditions affecting people in all geographic settings. We applied our established drug repurposing methods to one EML agent, N-acetylcysteine (NAC), to identify additional uses of relevance to the global health community beyond its existing EML indication (acetaminophen toxicity). Methods: We undertook a phenome-wide association study (PheWAS) of a variant in the glutathione synthetase ( Results: PheWAS of Conclusions: This body of literature indicates efficacy and safety of NAC in non-acetaminophen induced ALF. Given the presence of NAC on the EML, this medication is likely to be available across a range of resource settings; promulgating its use in this novel subset of ALF can provide healthcare professionals and patients with a valuable and safe complement to supportive care for this disease.
Language	English
Publishing date	2024-01-18
Publishing country	China
Document type	Journal Article
ISSN	2415-1289
ISSN (online)	2415-1289
DOI	10.21037/tgh-23-40
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Article ; Online: PheWAS-ME: a web-app for interactive exploration of multimorbidity patterns in PheWAS.

Strayer, Nick / Shirey-Rice, Jana K / Shyr, Yu / Denny, Joshua C / Pulley, Jill M / Xu, Yaomin

Bioinformatics (Oxford, England)

2020 Volume 37, Issue 12, Page(s) 1778–1780

Abstract: Summary: Electronic health records (EHRs) linked with a DNA biobank provide unprecedented opportunities for biomedical research in precision medicine. The Phenome-wide association study (PheWAS) is a widely used technique for the evaluation of ... ...

Abstract	Summary: Electronic health records (EHRs) linked with a DNA biobank provide unprecedented opportunities for biomedical research in precision medicine. The Phenome-wide association study (PheWAS) is a widely used technique for the evaluation of relationships between genetic variants and a large collection of clinical phenotypes recorded in EHRs. PheWAS analyses are typically presented as static tables and charts of summary statistics obtained from statistical tests of association between a genetic variant and individual phenotypes. Comorbidities are common and typically lead to complex, multivariate gene-disease association signals that are challenging to interpret. Discovering and interrogating multimorbidity patterns and their influence in PheWAS is difficult and time-consuming. We present PheWAS-ME: an interactive dashboard to visualize individual-level genotype and phenotype data side-by-side with PheWAS analysis results, allowing researchers to explore multimorbidity patterns and their associations with a genetic variant of interest. We expect this application to enrich PheWAS analyses by illuminating clinical multimorbidity patterns present in the data. Availability and implementation: A demo PheWAS-ME application is publicly available at https://prod.tbilab.org/phewas_me/. Sample datasets are provided for exploration with the option to upload custom PheWAS results and corresponding individual-level data. Online versions of the appendices are available at https://prod.tbilab.org/phewas_me_info/. The source code is available as an R package on GitHub (https://github.com/tbilab/multimorbidity_explorer). Supplementary information: Supplementary data are available at Bioinformatics online.
MeSH term(s)	Genome-Wide Association Study ; Genotype ; Humans ; Mobile Applications ; Multimorbidity ; Phenotype ; Polymorphism, Single Nucleotide
Language	English
Publishing date	2020-10-13
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	1422668-6
ISSN	1367-4811 ; 1367-4803
ISSN (online)	1367-4811
ISSN	1367-4803
DOI	10.1093/bioinformatics/btaa870
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Article ; Online: The Astounding Breadth of Health Disparity: Phenome-Wide Effects of Race on Disease Risk.

Pulley, Jill M / Jerome, Rebecca N / Bernard, Gordon R / Shirey-Rice, Jana K / Xu, Yaomin / Wilkins, Consuelo H

Journal of the National Medical Association

2020 Volume 113, Issue 2, Page(s) 187–194

Abstract: Objective: We conducted a phenotype-wide association study (PheWAS) to compare diagnoses among Blacks with those of Whites in one health center in Tennessee using data from 1,883,369 patients.: Methods: We used our deidentified EHR, the Synthetic ... ...

Abstract	Objective: We conducted a phenotype-wide association study (PheWAS) to compare diagnoses among Blacks with those of Whites in one health center in Tennessee using data from 1,883,369 patients. Methods: We used our deidentified EHR, the Synthetic Derivative, to assess risk of diagnoses associated with Black as compared with White race using Firth logistic regression with covariates including age, sex, and density of clinical encounters. Results: There were anchoring associations in both directions, including the highest increased risk for Blacks of having sickle cell anemia, and strongest decreased risk of basal cell carcinoma. Results included established areas of disparity and many novel associations. Conclusions: PheWAS is a viable tool for calculating risk associated with any biomarker. The current analysis provide a new approach to generating hypotheses and understanding the breadth of health disparities. Future analyses will further explore causality, risk factors, and potential confounders not accounted for here.
MeSH term(s)	Humans ; Logistic Models ; Phenotype ; Risk Factors ; Tennessee/epidemiology
Keywords	covid19
Language	English
Publishing date	2020-09-18
Publishing country	United States
Document type	Journal Article
ZDB-ID	419737-9
ISSN	1943-4693 ; 0027-9684
ISSN (online)	1943-4693
ISSN	0027-9684
DOI	10.1016/j.jnma.2020.08.009
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Article ; Online: Leveraging Human Genetics to Identify Safety Signals Prior to Drug Marketing Approval and Clinical Use.

Jerome, Rebecca N / Joly, Meghan Morrison / Kennedy, Nan / Shirey-Rice, Jana K / Roden, Dan M / Bernard, Gordon R / Holroyd, Kenneth J / Denny, Joshua C / Pulley, Jill M

Drug safety

2020 Volume 43, Issue 6, Page(s) 567–582

Abstract: Introduction: When a new drug or biologic product enters the market, its full spectrum of side effects is not yet fully understood, as use in the real world often uncovers nuances not suggested within the relatively narrow confines of preapproval ... ...

Abstract	Introduction: When a new drug or biologic product enters the market, its full spectrum of side effects is not yet fully understood, as use in the real world often uncovers nuances not suggested within the relatively narrow confines of preapproval preclinical and trial work. Objective: We describe a new, phenome-wide association study (PheWAS)- and evidence-based approach for detection of potential adverse drug effects. Methods: We leveraged our established platform, which integrates human genetic data with associated phenotypes in electronic health records from 29,722 patients of European ancestry, to identify gene-phenotype associations that may represent known safety issues. We examined PheWAS data and the published literature for 16 genes, each of which encodes a protein targeted by at least one drug or biologic product. Results: Initial data demonstrated that our novel approach (safety ascertainment using PheWAS [SA-PheWAS]) can replicate published safety information across multiple drug classes, with validated findings for 13 of 16 gene-drug class pairs. Conclusions: By connecting and integrating in vivo and in silico data, SA-PheWAS offers an opportunity to supplement current methods for predicting or confirming safety signals associated with therapeutic agents.
MeSH term(s)	Drug Approval ; Drug-Related Side Effects and Adverse Reactions/epidemiology ; Drug-Related Side Effects and Adverse Reactions/genetics ; Electronic Health Records ; Genome-Wide Association Study ; Humans ; Phenotype ; White People
Language	English
Publishing date	2020-04-21
Publishing country	New Zealand
Document type	Journal Article ; Research Support, N.I.H., Extramural
ZDB-ID	1018059-x
ISSN	1179-1942 ; 0114-5916
ISSN (online)	1179-1942
ISSN	0114-5916
DOI	10.1007/s40264-020-00915-6
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Article: Human and Machine Intelligence Together Drive Drug Repurposing in Rare Diseases.

Challa, Anup P / Zaleski, Nicole M / Jerome, Rebecca N / Lavieri, Robert R / Shirey-Rice, Jana K / Barnado, April / Lindsell, Christopher J / Aronoff, David M / Crofford, Leslie J / Harris, Raymond C / Alp Ikizler, T / Mayer, Ingrid A / Holroyd, Kenneth J / Pulley, Jill M

Frontiers in genetics

2021 Volume 12, Page(s) 707836

Abstract: Repurposing is an increasingly attractive method within the field of drug development for its efficiency at identifying new therapeutic opportunities among approved drugs at greatly reduced cost and time of more traditional methods. Repurposing has ... ...

Abstract	Repurposing is an increasingly attractive method within the field of drug development for its efficiency at identifying new therapeutic opportunities among approved drugs at greatly reduced cost and time of more traditional methods. Repurposing has generated significant interest in the realm of rare disease treatment as an innovative strategy for finding ways to manage these complex conditions. The selection of which agents should be tested in which conditions is currently informed by both human and machine discovery, yet the appropriate balance between these approaches, including the role of artificial intelligence (AI), remains a significant topic of discussion in drug discovery for rare diseases and other conditions. Our drug repurposing team at Vanderbilt University Medical Center synergizes machine learning techniques like phenome-wide association study-a powerful regression method for generating hypotheses about new indications for an approved drug-with the knowledge and creativity of scientific, legal, and clinical domain experts. While our computational approaches generate drug repurposing hits with a high probability of success in a clinical trial, human knowledge remains essential for the hypothesis creation, interpretation, "go-no go" decisions with which machines continue to struggle. Here, we reflect on our experience synergizing AI and human knowledge toward realizable patient outcomes, providing case studies from our portfolio that inform how we balance human knowledge and machine intelligence for drug repurposing in rare disease.
Language	English
Publishing date	2021-07-28
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2606823-0
ISSN	1664-8021
ISSN	1664-8021
DOI	10.3389/fgene.2021.707836
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Article ; Online: Interactive network-based clustering and investigation of multimorbidity association matrices with associationSubgraphs.

Bioinformatics (Oxford, England)

2022 Volume 39, Issue 1

Abstract: Motivation: Making sense of networked multivariate association patterns is vitally important to many areas of high-dimensional analysis. Unfortunately, as the data-space dimensions grow, the number of association pairs increases in O(n2); this means ... ...

Abstract	Motivation: Making sense of networked multivariate association patterns is vitally important to many areas of high-dimensional analysis. Unfortunately, as the data-space dimensions grow, the number of association pairs increases in O(n2); this means that traditional visualizations such as heatmaps quickly become too complicated to parse effectively. Results: Here, we present associationSubgraphs: a new interactive visualization method to quickly and intuitively explore high-dimensional association datasets using network percolation and clustering. The goal is to provide an efficient investigation of association subgraphs, each containing a subset of variables with stronger and more frequent associations among themselves than the remaining variables outside the subset, by showing the entire clustering dynamics and providing subgraphs under all possible cutoff values at once. Particularly, we apply associationSubgraphs to a phenome-wide multimorbidity association matrix generated from an electronic health record and provide an online, interactive demonstration for exploring multimorbidity subgraphs. Availability and implementation: An R package implementing both the algorithm and visualization components of associationSubgraphs is available at https://github.com/tbilab/associationsubgraphs. Online documentation is available at https://prod.tbilab.org/associationsubgraphs_info/. A demo using a multimorbidity association matrix is available at https://prod.tbilab.org/associationsubgraphs-example/.
MeSH term(s)	Software ; Multimorbidity ; Algorithms ; Cluster Analysis ; Phenomics
Language	English
Publishing date	2022-12-01
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	1422668-6
ISSN	1367-4811 ; 1367-4803
ISSN (online)	1367-4811
ISSN	1367-4803
DOI	10.1093/bioinformatics/btac780
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Article ; Online: Using What We Already Have: Uncovering New Drug Repurposing Strategies in Existing Omics Data.

Pulley, Jill M / Rhoads, Jillian P / Jerome, Rebecca N / Challa, Anup P / Erreger, Kevin B / Joly, Meghan M / Lavieri, Robert R / Perry, Kelly E / Zaleski, Nicole M / Shirey-Rice, Jana K / Aronoff, David M

Annual review of pharmacology and toxicology

2019 Volume 60, Page(s) 333–352

Abstract: The promise of drug repurposing is to accelerate the translation of knowledge to treatment of human disease, bypassing common challenges associated with drug development to be more time- and cost-efficient. Repurposing has an increased chance of success ... ...

Abstract	The promise of drug repurposing is to accelerate the translation of knowledge to treatment of human disease, bypassing common challenges associated with drug development to be more time- and cost-efficient. Repurposing has an increased chance of success due to the previous validation of drug safety and allows for the incorporation of omics. Hypothesis-generating omics processes inform drug repurposing decision-making methods on drug efficacy and toxicity. This review summarizes drug repurposing strategies and methodologies in the context of the following omics fields: genomics, epigenomics, transcriptomics, proteomics, metabolomics, microbiomics, phenomics, pregomics, and personomics. While each omics field has specific strengths and limitations, incorporating omics into the drug repurposing landscape is integral to its success.
MeSH term(s)	Animals ; Decision Making ; Drug Development/economics ; Drug Development/methods ; Drug Repositioning/methods ; Drug-Related Side Effects and Adverse Reactions/prevention & control ; Humans ; Pharmaceutical Preparations/administration & dosage
Chemical Substances	Pharmaceutical Preparations
Language	English
Publishing date	2019-07-23
Publishing country	United States
Document type	Journal Article ; Review
ZDB-ID	196587-6
ISSN	1545-4304 ; 0362-1642
ISSN (online)	1545-4304
ISSN	0362-1642
DOI	10.1146/annurev-pharmtox-010919-023537
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Article ; Online: A Phenome-Wide Association Study Uncovers a Pathological Role of Coagulation Factor X during

Choby, Jacob E / Monteith, Andrew J / Himmel, Lauren E / Margaritis, Paris / Shirey-Rice, Jana K / Pruijssers, Andrea / Jerome, Rebecca N / Pulley, Jill / Skaar, Eric P

Infection and immunity

2019 Volume 87, Issue 5

Abstract: Coagulation and inflammation are interconnected, suggesting that coagulation plays a key role in the inflammatory response to pathogens. A phenome-wide association study (PheWAS) was used to identify clinical phenotypes of patients with a polymorphism in ...

Abstract	Coagulation and inflammation are interconnected, suggesting that coagulation plays a key role in the inflammatory response to pathogens. A phenome-wide association study (PheWAS) was used to identify clinical phenotypes of patients with a polymorphism in coagulation factor X. Patients with this single nucleotide polymorphism (SNP) were more likely to be hospitalized with hemostatic and infection-related disorders, suggesting that factor X contributes to the immune response to infection. To investigate this, we modeled infections by human pathogens in a mouse model of factor X deficiency. Factor X-deficient mice were protected from systemic
MeSH term(s)	Acinetobacter Infections/immunology ; Acinetobacter Infections/physiopathology ; Acinetobacter baumannii/immunology ; Animals ; Disease Models, Animal ; Factor X/genetics ; Factor X/immunology ; Host-Pathogen Interactions/genetics ; Host-Pathogen Interactions/immunology ; Humans ; Mice ; Mice, Inbred C57BL ; Phenotype ; Polymorphism, Genetic
Chemical Substances	Factor X (9001-29-0)
Language	English
Publishing date	2019-04-23
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	218698-6
ISSN	1098-5522 ; 0019-9567
ISSN (online)	1098-5522
ISSN	0019-9567
DOI	10.1128/IAI.00031-19
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Article ; Online: Systematically Prioritizing Candidates in Genome-Based Drug Repurposing.

Challa, Anup P / Lavieri, Robert R / Lewis, Judith T / Zaleski, Nicole M / Shirey-Rice, Jana K / Harris, Paul A / Aronoff, David M / Pulley, Jill M

Assay and drug development technologies

2019 Volume 17, Issue 8, Page(s) 352–363

Abstract: Drug repurposing is the application of approved drugs to treat diseases separate and distinct from their original indications. Herein, we define the scope of all practical precision drug repurposing using DrugBank, a publicly available database of ... ...

Abstract	Drug repurposing is the application of approved drugs to treat diseases separate and distinct from their original indications. Herein, we define the scope of all practical precision drug repurposing using DrugBank, a publicly available database of pharmacological agents, and BioVU, a large, de-identified DNA repository linked to longitudinal electronic health records at Vanderbilt University Medical Center. We present a method of repurposing candidate prioritization through integration of pharmacodynamic and marketing variables from DrugBank with quality control thresholds for genomic data derived from the DNA samples within BioVU. Through the synergy of delineated "target-action pairs," along with target genomics, we identify ∼230 "pairs" that represent all practical opportunities for genomic drug repurposing. From this analysis, we present a pipeline of 14 repurposing candidates across 7 disease areas that link to our repurposability platform and present high potential for randomized controlled trial startup in upcoming months.
MeSH term(s)	DNA ; Databases, Factual ; Drug Repositioning/methods ; Genome, Human/genetics ; Genomics ; Humans
Chemical Substances	DNA (9007-49-2)
Language	English
Publishing date	2019-11-26
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural
ISSN	1557-8127
ISSN (online)	1557-8127
DOI	10.1089/adt.2019.950
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Article ; Online: Advocating for mutually beneficial access to shelved compounds.

Pulley, Jill M / Jerome, Rebecca N / Shirey-Rice, Jana K / Zaleski, Nicole M / Naylor, Helen M / Pruijssers, Andrea J / Jackson, James C / Bernard, Gordon R / Holroyd, Kenneth J

Future medicinal chemistry

2018 Volume 10, Issue 12, Page(s) 1395–1398

MeSH term(s)	Antidiuretic Hormone Receptor Antagonists/therapeutic use ; Anxiety Disorders/drug therapy ; Depressive Disorder, Major/drug therapy ; Drug Industry ; Drug Repositioning/methods ; Humans ; Indoles/therapeutic use ; Pyrrolidines/therapeutic use ; Receptors, Vasopressin/therapeutic use
Chemical Substances	1-(5-chloro-1-((2,4-dimethoxyphenyl)sulfonyl)-3-(2-methoxyphenyl)-2-oxo-2,3-dihydro-1H-indol-3-yl)-4-hydroxy-N,N-dimethyl-2-pyrrolidinecarboxamide ; AVPR1b protein, human ; Antidiuretic Hormone Receptor Antagonists ; Indoles ; Pyrrolidines ; Receptors, Vasopressin
Language	English
Publishing date	2018-05-23
Publishing country	England
Document type	Editorial ; Research Support, N.I.H., Extramural
ISSN	1756-8927
ISSN (online)	1756-8927
DOI	10.4155/fmc-2018-0090
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