Small Molecule Metabolites as Predictive Biomarkers for Cardiovascular Risk of Exposure to 16O Radiation

Khyati Mehta (Mentor: Dr. Amrita Cheema, Department of Oncology and Biochemistry and Molecular & Cellular Biology; Co-Director of Proteomics and Metabolomics Shared Resource, Georgetown University Medical Center)

December 14th, 2016, 2:00pm, Room 341, Basic Science

During space travel, astronauts are at risk of exposure to radiation from galactic cosmic rays, solar emissions, and solar proton events.  Although there is an evidence of pathophysiological changes in cellular function, epigenetics, and gene expression are shown resulting in an altered metabolism in response to radiation exposure, the full effects of radiation exposure (especially in the context of space radiation) is not  fully understood.   

In this study 150 male C57BL/6 mice at 6 months of age were exposed to either oxygen ions (600 MeV/n) at doses of 0.1, 0.25, or 1 Gy, proton radiation at 0.5 or1 Gy, or gamma radiation at 0.5, 1, or 3 Gy.  Left ventricle tissue samples were collected after either 14 or 90 days of irradiation.  Sample were subject to untargeted profiling via UPLLC-ESI-QTOF-MS.  Raw data were pre-processed using XCMS software (Scripps Institute). Our goal was to study time and dose dependent effects of radiation exposure.

Statistical analysis using R was conducted.  The data were normalized based on the QCs.  After normalization, the data were subjected to a logarithmic transformation and scaled using pareto.  ANOVA for time and dose comparisons and Student’s t-test for binary comparisons was performed.  Given the large dataset and number of statistical tests performed, a multiple comparison adjustment method, Benjamini-Hochberg, was applied to control the false discover rate (FDR).   M/z’s with FDR values lower than 0.05 were selected for identification.  Those m/z values that were identified as biologically relevant were validated by running the samples for tandem mass spectrometry (MS/MS).  The MS/MS spectra obtained was matched to available spectra online for identification of the biomarker.  In summary, several metabolites were identified as potential predictive biomarkers of exposure to 16O radiation.  Up-regulated metabolites include glucose 1-phosphate, deoxyguanosine diphosphate (dGDP), and ubiquinone-4.  Down-regulated metabolites include PG(16:0/0:0) and 1α,25-dihydroxy-11-(4-hydroxymethylphenyl)-9,11-didehydrovitamin D3. The implication of these biochemical changes with the overall phenotype will be investigated in future.