Evaluating the influences of confounding variables on benchmark dose using a case study in the field of ionizing radiation

Abstract

Purpose

A vast amount of data regarding the effects of radiation stressors on transcriptional changes has been produced over the past few decades. These data have shown remarkable consistency across platforms and experimental design, enabling increased understanding of early molecular effects of radiation exposure. However, the value of transcriptomic data in the context of risk assessment is not clear and represents a gap that is worthy of further consideration. Recently, benchmark dose (BMD) modeling has shown promise in correlating a transcriptional point of departure (POD) to that derived using phenotypic outcomes relevant to human health risk assessment. Although frequently applied in chemical toxicity evaluation, our group has recently demonstrated application within the field of radiation research. This approach allows the possibility to quantitatively compare radiation-induced gene and pathway alterations across various datasets using BMD values and derive meaningful biological effects. However, before BMD modeling can confidently be used, an understanding of the impact of confounding variables on BMD outputs is needed.

Methods

To this end, BMD modeling was applied to a publicly available microarray dataset (Gene Expression Omnibus #GSE23515) that used peripheral blood ex-vivo gamma-irradiated at 0.82 Gy/min, at doses of 0, 0.1, 0.5 or 2 Gy, and assessed 6 hours post-exposure. The dataset comprised six female smokers (F-S), six female nonsmokers (F-NS), six male smokers (M-S), and six male nonsmokers (M-NS).

Results

A combined total of 412 genes were fit to models and the BMD distribution was noted to be bi-modal across the four groups. A total of 74, 41, 62 and 62 genes were unique to the F-NS, M-NS, F-S and M-S groups. Sixty-two BMD modeled genes and nine pathways were common across all four groups. There were no differential sensitivity of BMD responses in the robust common genes and pathways.

Conclusion

For radiation-responsive genes and pathways common across the study groups, the BMD distribution of transcriptional activity was unaltered by sex and smoking status. Although further validation of the data is needed, these initial findings suggest BMD values for radiation relevant genes and pathways are robust and could be explored further in future studies.

Keywords:

• Radiation
• BMD
• transcriptomics
• benchmark dose modeling
• confounding factors

Acknowledgments

The authors would like to acknowledge Drs. Katya Feder and Robert Stainforth for insightful comments and edits to the manuscript. This work was funded by the Genomics Research and Development Initiative. CLY acknowledges support from the Canada Research Chairs Program.

Disclosure statement

The authors declare they have no competing interests.

Additional information

Notes on contributors

Nadine Adam

Nadine J. Adam, M.Sc., is a Laboratory Biologist at Health Canada, and she previously worked with the Consumer and Clinical Radiation Protection Bureau. She completed her M.Sc. studies in Biochemistry at the University of Ottawa.

Ngoc Q. Vuong

Ngoc Q. Vuong, Ph.D, is a Senior Technician at the Radiation Protection Bureau (RPB) of Health Canada. He graduated from the University of Ottawa with a Ph.D degree in Biochemistry (specialized in environmental toxicology). He joined the RPB in 2018, and he supports projects in both the RPB and the Consumer and Clinical Radiation Protection Bureau.

Hailey Adams

Hailey Adams, B.Sc., is a Laboratory Biologist at Health Canada, and she previously worked with the Consumer and Clinical Radiation Protection Bureau. She completed B.Sc. studies in Biology and Biotechnology at Carleton University.

Byron Kuo

Byron Kuo, M.Sc., is a Computational Biologist at Health Canada.

Afshin Beheshti

Afshin Beheshti, Ph.D., is a Principal Investigator and Bioinformatician at KBR at NASA Ames Research Center, a Visiting Researcher at Broad Institute of MIT and Harvard, and President of a nonprofit formed on March 2020 working on COVID-19 called COVID-19 International Research Team (COV-IRT, www.cov-irt.org). His research interests include applying systems biology approaches to a broad range of topics which include: mitochondria, noncoding RNAs/miRNAs, radiation biology, space biology, cancer, COVID-19, and cardiovascular disease.

Carole Yauk

Carole Yauk, Ph.D., is a Professor in the Department of Biology, University of Ottawa, where she holds the Canada Research Chair in Genomics and the Environment. Dr. Yauk serves as a Canadian delegate to the OECD's Extended Advisory Group on Molecular Screening and Toxicogenomics. Within this group, she contributed to the development of the AOP Users' Handbook and is an AOP developer and reviewer.

Ruth Wilkins

Ruth C. Wilkins, Ph.D, is a Research Scientist at the Consumer and Clinical Radiation Protection Bureau of Health Canada and the Chief of the Ionizing Radiation Health Sciences Division. She graduated with a Ph.D in Medical Physics from Carleton University and has been employed at Health Canada for the past 25 years. She is an Adjunct Professor and lecturer in Radiobiology in the Department of Physics at Carleton University and the alternative representative of Canada to the United Nations Scientific Committee on the Effects of Atomic Radiation (UNSCEAR).

Vinita Chauhan

Vinita Chauhan, Ph.D, is a Senior Research Scientist at the Consumer and Clinical Radiation Protection Bureau of Health Canada. She is a Canadian delegate of the HLG-LDR and Extended Advisory Group on Molecular Screening and Toxicogenomics (EAGMST) of the OECD. She chairs the HLG-LDR Rad/Chem AOP Joint Topical Group and is the co-founder of Canadian Organization of Health Effects from Radiation Exposure (COHERE) initiative.