About

Ivan Rusyn is associated with the Texas A&M College of Veterinary Medicine & Biomedical Sciences, which is ranked as the No. 3 veterinary college in the United States and is engaged in cutting-edge basic and clinical research. His work involves innovative research that addresses complex scientific questions through a 'One Health' approach, recognizing the interactions between animal, human, and environmental health. The college emphasizes translational research that bridges basic and clinical sciences, reflecting Rusyn's focus on proactive solutions for health issues affecting animals, humans, and the environment. His contributions are part of a broader institutional effort to support collaborations that turn discoveries into practical applications for health and well-being.

Research topics

• Computer Science
• Biology
• Medicine
• Engineering
• Genetics
• Pharmacology
• Computer Security
• Internal medicine
• Pathology
• Risk analysis (engineering)
• Library science
• Toxicology
• Gerontology
• Ecology
• Artificial Intelligence
• Management science
• Environmental science
• Computational biology
• Cell biology
• Veterinary medicine
• Environmental chemistry
• Geography
• Family medicine
• Chemistry

Selected publications

• The COVID-19 Pandemic Vulnerability Index (PVI) Dashboard: Monitoring County-Level Vulnerability Using Visualization, Statistical Modeling, and Machine Learning

  Environmental Health Perspectives · 2021 · 93 citations

  • Computer Science
  • Library science
  • Geography
  DOI

• Emerging technologies and their impact on regulatory science

  Experimental Biology and Medicine · 2021 · 94 citations

  • Computer Science
  • Risk analysis (engineering)
  • Computer Science

  technologies and novel approaches for safety assessment of food, drugs, and personal care products. Convergence of these emerging technologies is also enabling rapid advances and approaches that may impact regulatory decisions and approvals. Although the development of emerging technologies may allow rapid advances in regulatory decision making, there is concern that these new technologies have not been thoroughly evaluated to determine if they are ready for regulatory application, singularly or in combinations. The magnitude of these combined technical advances may outpace the ability to assess fit for purpose and to allow routine application of these new methods for regulatory purposes. There is a need to develop strategies to evaluate the new technologies to determine which ones are ready for regulatory use. The opportunity to apply these potentially faster, more accurate, and cost-effective approaches remains an important goal to facilitate their incorporation into regulatory use. However, without a clear strategy to evaluate emerging technologies rapidly and appropriately, the value of these efforts may go unrecognized or may take longer. It is important for the regulatory science field to keep up with the research in these technically advanced areas and to understand the science behind these new approaches. The regulatory field must understand the critical quality attributes of these novel approaches and learn from each other's experience so that workforces can be trained to prepare for emerging global regulatory challenges. Moreover, it is essential that the regulatory community must work with the technology developers to harness collective capabilities towards developing a strategy for evaluation of these new and novel assessment tools.

  DOI

• A new approach method for characterizing inter-species toxicodynamic variability

  Journal of Toxicology and Environmental Health · 2021 · 18 citations

  Senior authorCorresponding
  • Biology
  • Toxicology
  • Ecology

  or alternative approaches, extending the strategy to replace use of default adjustment factors with experimental characterization of toxicodynamic inter-individual variability and to also address toxicodynamic inter-species variability.

  DOI

• Key Characteristics of Human Hepatotoxicants as a Basis for Identification and Characterization of the Causes of Liver Toxicity

  Hepatology · 2021 · 77 citations

  1st authorCorresponding
  • Computer Science
  • Computer Security
  • Computational biology

  Hazard identification regarding adverse effects on the liver is a critical step in safety evaluations of drugs and other chemicals. Current testing paradigms for hepatotoxicity rely heavily on preclinical studies in animals and human data (epidemiology and clinical trials). Mechanistic understanding of the molecular and cellular pathways that may cause or exacerbate hepatotoxicity is well advanced and holds promise for identification of hepatotoxicants. One of the challenges in translating mechanistic evidence into robust decisions about potential hepatotoxicity is the lack of a systematic approach to integrate these data to help identify liver toxicity hazards. Recently, marked improvements were achieved in the practice of hazard identification of carcinogens, female and male reproductive toxicants, and endocrine disrupting chemicals using the key characteristics approach. Here, we describe the methods by which key characteristics of human hepatotoxicants were identified and provide examples for how they could be used to systematically identify, organize, and use mechanistic data when identifying hepatotoxicants.

  DOI

• Cardiovascular Effects of Polychlorinated Biphenyls and Their Major Metabolites

  Environmental Health Perspectives · 2020 · 61 citations

  Senior authorCorresponding
  • Library science
  • Medicine
  • Gerontology

  BACKGROUND: new approach methods data. OBJECTIVES: . METHODS: flux in CMs and inhibition of tubulogenesis in ECs. High-content imaging was used to evaluate cytotoxicity, mitochondrial integrity, and oxidative stress. RESULTS: cardiovascular effects of PCBs. Oxidation of PCBs, especially to di-hydroxylated and quinone metabolites, was associated with the most pronounced effects, whereas sulfation and methoxylation of PCBs resulted in diminished bioactivity. DISCUSSION: data can be used to characterize human health risks from PCBs and their metabolites. https://doi.org/10.1289/EHP7030.

  DOI

• Epithelial splicing regulatory protein 2–mediated alternative splicing reprograms hepatocytes in severe alcoholic hepatitis

  Journal of Clinical Investigation · 2020 · 77 citations

  • Biology
  • Cancer research
  • Cell biology

  Severe alcoholic hepatitis (SAH) is a deadly liver disease without an effective medical therapy. Although SAH mortality is known to correlate with hepatic accumulation of immature liver cells, why this occurs and how it causes death are unclear. Here, we demonstrate that expression of epithelial splicing regulatory protein 2 (ESRP2), an RNA-splicing factor that maintains the nonproliferative, mature phenotype of adult hepatocytes, was suppressed in both human SAH and various mouse models of SAH in parallel with the severity of alcohol consumption and liver damage. Inflammatory cytokines released by excessive alcohol ingestion reprogrammed adult hepatocytes into proliferative, fetal-like cells by suppressing ESRP2. Sustained loss of ESRP2 permitted reemergence of a fetal RNA-splicing program that attenuates the Hippo signaling pathway and thus allows fetal transcriptional regulators to accumulate in adult liver. We further showed that depleting ESRP2 in mice exacerbated alcohol-induced steatohepatitis, enabling surviving hepatocytes to shed adult hepatocyte functions and become more regenerative, but threatening overall survival by populating the liver with functionally immature hepatocytes. Our findings revealed a mechanism that explains why liver failure develops in patients with the clinical syndrome of SAH, suggesting that recovery from SAH might be improved by limiting adult-to-fetal reprogramming in hepatocytes.

  DOI

• Risk Characterization of Environmental Samples Using<i>In Vitro</i>Bioactivity and Polycyclic Aromatic Hydrocarbon Concentrations Data

  Toxicological Sciences · 2020 · 51 citations

  Senior authorCorresponding
  • Environmental chemistry
  • Chemistry
  • Environmental science

  Methods to assess environmental exposure to hazardous chemicals have primarily focused on quantification of individual chemicals, although chemicals often occur in mixtures, presenting challenges to the traditional risk characterization framework. Sampling sites in a defined geographic region provide an opportunity to characterize chemical contaminants, with spatial interpolation as a tool to provide estimates for non-sampled sites. At the same time, the use of in vitro bioactivity measurements has been shown to be informative for rapid risk-based decisions. In this study, we measured in vitro bioactivity in 39 surface soil samples collected immediately after flooding associated with Hurricane Harvey in Texas in a residential area known to be inundated with polycyclic aromatic hydrocarbon (PAH) contaminants. Bioactivity data were from a number of functional and toxicity assays in 5 human cell types, such as induced pluripotent stem cell-derived hepatocytes, cardiomyocytes, neurons, and endothelial cells, as well as human umbilical vein endothelial cells. Data on concentrations of PAH in these samples were also available and the combination of data sources offered a unique opportunity to assess the joint spatial variation of PAH components and bioactivity. We found significant evidence of spatial correlation of a subset of PAH contaminants and of cell-based phenotypes. In addition, we show that the cell-based bioactivity data can be used to predict environmental concentrations for several PAH contaminants, as well as overall PAH summaries and cancer risk. This study's impact lies in its demonstration that cell-based profiling can be used for rapid hazard screening of environmental samples by anchoring the bioassays to concentrations of PAH. This work sets the stage for identification of the areas of concern and direct quantitative risk characterization based on bioactivity data, thereby providing an important supplement to traditional individual chemical analyses by shedding light on constituents that may be missed from targeted chemical monitoring.

  DOI

• Integrative QTL analysis of gene expression and chromatin accessibility identifies multi-tissue patterns of genetic regulation

  PLoS Genetics · 2020 · 58 citations

  • Biology
  • Genetics

  Gene transcription profiles across tissues are largely defined by the activity of regulatory elements, most of which correspond to regions of accessible chromatin. Regulatory element activity is in turn modulated by genetic variation, resulting in variable transcription rates across individuals. The interplay of these factors, however, is poorly understood. Here we characterize expression and chromatin state dynamics across three tissues-liver, lung, and kidney-in 47 strains of the Collaborative Cross (CC) mouse population, examining the regulation of these dynamics by expression quantitative trait loci (eQTL) and chromatin QTL (cQTL). QTL whose allelic effects were consistent across tissues were detected for 1,101 genes and 133 chromatin regions. Also detected were eQTL and cQTL whose allelic effects differed across tissues, including local-eQTL for Pik3c2g detected in all three tissues but with distinct allelic effects. Leveraging overlapping measurements of gene expression and chromatin accessibility on the same mice from multiple tissues, we used mediation analysis to identify chromatin and gene expression intermediates of eQTL effects. Based on QTL and mediation analyses over multiple tissues, we propose a causal model for the distal genetic regulation of Akr1e1, a gene involved in glycogen metabolism, through the zinc finger transcription factor Zfp985 and chromatin intermediates. This analysis demonstrates the complexity of transcriptional and chromatin dynamics and their regulation over multiple tissues, as well as the value of the CC and related genetic resource populations for identifying specific regulatory mechanisms within cells and tissues.

  DOI

Recent grants

• NIH Grant R01ES023195

  NIH · $2.2M · 2018

• TEX-VAL: Texas A&M Tissue Chip Validation Consortium

  NIH · $3.0M · 2018–2022

• NIH Grant R01AA016258

  NIH · $2.5M · 2011

• TEX-VAL: Texas A&M Tissue Chip Validation Center

  NIH · $4.2M · 2016–2019

• NIH Grant R01ES015241

  NIH · $3.1M · 2013

Frequent coauthors

• Weihsueh A. Chiu

  Texas A&M University

  118 shared

• Igor P. Pogribny

  National Center for Toxicological Research

  92 shared

• Fred A. Wright

  90 shared

• Hiroshi Kono

  Ishikiriseiki Hospital

  60 shared

• Oksana Kosyk

  57 shared

• Ronald G. Thurman

  55 shared

• Blair U. Bradford

  The Hamner Institutes for Health Sciences

  54 shared

• Frederick A. Beland

  National Center for Toxicological Research

  48 shared

Similar researchers at Texas A&M University

• Stephen Safeh-131
• Raymond Carrollh-119
• Fuller Bazerh-114
• Renyi Zhangh-106
• Kim Dunbarh-103