Date of Award
2024
Degree Type
Dissertation
Degree Name
Doctor of Philosophy in Physics
Department
Physics
First Advisor
Michael Antosh
Abstract
Radiation Biodosimetry is a crucial method for evaluating the biological consequences of radiation exposure on health outcomes. This technique estimates radiation dose by analyzing the biological effects it causes in the body becomes especially valuable in situations where traditional physical dosimeters, like badges, are unavailable or unreliable. In these scenarios, Radiation Biodosimetry enables accurate dose assessment, which is critical for making informed decisions during emergency response (triage), treatment planning, and long-term health risk evaluation.
Current biodosimetry methods struggle to accurately estimate radiation doses, especially for low-dose exposures or complex scenarios involving both neutrons and photons, like those arising from improvised nuclear devices. As a first step towards this goal, we designed and administered tailored radiation doses to human blood samples at two nuclear research facilities, Radiological Research Accelerator Facility at Columbia University (RARAF) and Rhode Island Nuclear Science Center (RINSC), allowing us to analyze the impact of neutrons alongside photons in a controlled setting. The RARAF facility employs a neutron irradiator delivering a broad spectrum of neutron energies, unlike RINSC which utilizes thermal neutrons with a significantly lower energy. This dissertation investigates the impacts of neutron radiation on biological responses using diverse experimental designs.
In Chapter 1, to understand the underlying mechanisms of gene expression changes, Differential expression analysis for sequence count data (DESeq2) was utilized to perform the differential gene expression analysis. Three distinct approaches were implemented to achieve a more in-depth understanding. Method 1 prioritized the impact of various radiation doses (Condition) 0.5 Gy, 1 Gy, 2 Gy, and 4 Gy and the radiation source (Batch) at two facilities RARAF and RINSC. Expanding on Method 1, Method 2 approach incorporated the potential influence of sex in addition to the radiation dose and source. Similar to Method 2, Method 3 investigated the potential impact of age as an additional factor alongside condition and source. Our findings demonstrate a significantly greater response in genes differentially expressed by neutron radiation at the RARAF facility compared to exposures at the nuclear reactor, RINSC. This observation highlights unique patterns of gene expression in response to neutron irradiation, with variations influenced by both dose and exposure duration at each facility. The age comparisons in chapters 1 and 2 may be limited by differences in sample size. This could be due to a lack of statistical power to detect age related effects. Future studies with more balanced group sizes are needed to confirm the observed age effects on gene expression.
In Chapter 2, besides identifying gene expression biomarkers, we utilized Database for Annotation, Visualization, and Integrated Discovery (DAVID), a bioinformatics tool to analyze the broader biological impact of radiation-induced gene expression changes. This study investigated the effects of neutron radiation exposure on gene activity at two facilities RARAF and RINSC. The analysis revealed a significant impact on genes involved in two key processes: p53 signaling pathway and DNA damage response. Interestingly, this effect was observed at both facilities, and across all radiation doses administered at 0.5 Gy, 1 Gy, 2 Gy, 4 Gy. This suggests that even at lower doses, gene expression related to DNA repair and the p53 pathway was activated. Notably, at the RARAF facility, we observed a significant increase in genes associated with cancer development as low as 0.5 Gy of radiation dose. This suggests that these processes play a key role in the physiological response to radiation exposure.
In Chapter 3, to further explore the similarities between gene expression patterns in the RARAF and RINSC groups across different dose and sex combinations, we employed the algorithm - Comparison of Ranked Lists for Analysis of Gene Expression Data (CORaL). This analysis involved calculating fold changes using the normalized gene expression values separately for each facility RARAF and RINSC using two distinct filtering approaches. In Method 1, a threshold of 40 transcripts per million (TPM) was applied to normalized data to ensure analysis of genes with higher expression and minimize the influence of low-abundance transcripts. Fold changes were then calculated for each dose group 0.5 Gy, 1 Gy, 2 Gy, and 4 Gy relative to the control group for the same sex and facility (e.g., RARAF female control for female samples). In Method 2, DESeq2's independent filtering approach was used to pre-process data for analyzing gene expression across varying radiation doses 0.5 Gy, 1 Gy, 2 Gy, and 4 Gy within both RARAF and RINSC treatment groups. This method identifies and removes genes with consistently low expression levels, using an automatically determined threshold of 0.8481184. Fold changes were determined using the same approach employed in Method 1. Method 3 and Method 4 further investigates gene expression patterns by building upon the pre-filtering step used in Method 1 and Method 2 respectively. Average expression values were computed for four subgroups: female and male samples in both the RARAF and RINSC facilities, and across all radiation doses 0.5 Gy, 1 Gy, 2 Gy, 4 Gy. Within each subgroup, separate averages were calculated for control samples and each radiation dose group. These average expression values were subsequently used to calculate fold changes. This study focused on the factors influencing gene expression patterns after radiation exposure using multiple clustering methods. Sex emerged as a major factor influencing gene expression, with distinct clustering patterns observed for males and females in Method 3 and Method 4. This highlights the importance of considering sex as a biological variable in radiation response studies. Shared genetic background consistently influenced gene expression across all clusters. Samples from the same donor consistently grouped together, emphasizing its strong effect. However, further investigation is needed to confirm the extent of this influence. Several clusters displayed interconnectedness that transcended factors like sex, dose, or treatment facility. This suggests the involvement of additional, unmeasured biological variations or technical factors that necessitate further exploration. Future studies with more detailed information on influencing factors including sex, dose, or treatment facility are needed to fully understand the underlying mechanism.
Recommended Citation
Basavaraj, Rashmi, "DIFFERENTIAL GENE EXPRESSION ANALYSIS: GENOMIC RESPONSE IN HUMAN PERIPHERAL BLOOD FOLLOWING NEUTRON EXPOSURE FOR RADIATION BIODOSIMETRY APPLICATIONS" (2024). Open Access Dissertations. Paper 1688.
https://digitalcommons.uri.edu/oa_diss/1688