Page 336 - 2014 Printable Abstract Book
P. 336
and LDR (0.0028 Gy/min) along with proper sham-irradiated controls. The effects of LDR and HDR IR
exposures were explored via liquid chromatography coupled with time of flight mass spectrometry at 2
days and 5 days post-IR exposure. A wide variety of statistical tools were employed to further focus on
metabolites, which showed responses to LDR IR exposure compared to metabolite markers previously
established for HDR exposures. From a total of 709 detected mass spectral features, 200 were determined
to be statistically significant when comparing urine from mice irradiated with HDR to that of sham-
irradiated mice 2 days post exposure. The number of statistically significant ions was 107, much lower in
the case of LDR irradiation. These metabolites were then subjected to different comparative analyses to
identify those displaying dose rate-specific responses to IR. The results of this study showed that LDR and
HDR exposures perturb many of the same pathways, which also were implicated in our previous IR studies.
However, it is important to note that LDR affected the levels of several metabolites differently than did
HDR. It was also observed that the urinary levels of many metabolites decreased over time post-exposure
while a few metabolites showed the opposite response. Once validated and confirmed in a separate study,
the differences in urinary excretion levels of these metabolites could potentially be used to assess an
individual’s exposure in a radiobiological event, and thus would have utility for both triage and injury
assessment. This study was supported by the National Institute of Health (National Institute of Allergy and
Infectious Diseases) grant U19 A1067773.
(PS6-20) Investigating the Specificity of the Human Urinary Radiation Metabolomic Signature:
1
1
Comparing Radiation to Sepsis and Trauma. Evagelia C. Laiakis ; Yiwen Wang, MS ; Adrian Agudelo ;
2
2
1
1
1
Simeng Suy ; Sean P. Collins, MD PhD ; Azra Bihorac, MD MS FCCM FASN ; and Albert J. Fornace Jr
1
2
Georgetown University, Washington, DC and University of Florida, Gainesville, FL
Radiological terrorism and accidents have emerged as a real threat in the past few years
throughout the world. While methods exist to quantify the radiation exposure and the future cancer risk
in an exposed individual (i.e. the gold standard being cytogenetics), these methods are laborious, require
specific technical expertise, and are not applicable in a real life situation where thousands need to be
triaged. For this, rapid, accurate, and non-invasive methods need to be developed. We recently published
on the radiation signature in urine of total body irradiated patients. While statistically significant
differences were observed between pre- and post-exposure, the specificity of the signature was not
investigated. In a real life situation, where victims may present with underlying conditions or trauma, it is
important to be able to distinguish in a reliable way those that require further triage based on radiation
exposure. For this purpose urine samples from patients presenting with sepsis or trauma were
investigated through metabolomics. Global metabolomic profiling was obtained through analysis with
Ultra Performance Liquid Chromatography (UPLC) coupled to time-of-flight mass spectrometry (TOFMS)
(Waters). Peak alignment and deconvolution of the chromatographic data were conducted with
MarkerLynx software (Waters, MA). Prior to further analysis, each sample was normalized to its respective
creatinine. Statistical analysis was conducted through the software MetaboLyzer and putative identities
were assigned based on the metabolite databases HMDB, KEGG, Lipidmaps, and BioCyc. An increased
number of acylcarnitines were noted in the trauma samples, distinct from the ones previously identified
in radiation samples. In contrast, sepsis samples show an increase in excretion of putative L-carnitine, the
basic component of all acylcarnitines. In addition, sepsis samples exhibit an increase in a number of amino
acids and methyl conjugates of guanine and guanosine. Developing therefore a panel of metabolites that
334 | P a g e
exposures were explored via liquid chromatography coupled with time of flight mass spectrometry at 2
days and 5 days post-IR exposure. A wide variety of statistical tools were employed to further focus on
metabolites, which showed responses to LDR IR exposure compared to metabolite markers previously
established for HDR exposures. From a total of 709 detected mass spectral features, 200 were determined
to be statistically significant when comparing urine from mice irradiated with HDR to that of sham-
irradiated mice 2 days post exposure. The number of statistically significant ions was 107, much lower in
the case of LDR irradiation. These metabolites were then subjected to different comparative analyses to
identify those displaying dose rate-specific responses to IR. The results of this study showed that LDR and
HDR exposures perturb many of the same pathways, which also were implicated in our previous IR studies.
However, it is important to note that LDR affected the levels of several metabolites differently than did
HDR. It was also observed that the urinary levels of many metabolites decreased over time post-exposure
while a few metabolites showed the opposite response. Once validated and confirmed in a separate study,
the differences in urinary excretion levels of these metabolites could potentially be used to assess an
individual’s exposure in a radiobiological event, and thus would have utility for both triage and injury
assessment. This study was supported by the National Institute of Health (National Institute of Allergy and
Infectious Diseases) grant U19 A1067773.
(PS6-20) Investigating the Specificity of the Human Urinary Radiation Metabolomic Signature:
1
1
Comparing Radiation to Sepsis and Trauma. Evagelia C. Laiakis ; Yiwen Wang, MS ; Adrian Agudelo ;
2
2
1
1
1
Simeng Suy ; Sean P. Collins, MD PhD ; Azra Bihorac, MD MS FCCM FASN ; and Albert J. Fornace Jr
1
2
Georgetown University, Washington, DC and University of Florida, Gainesville, FL
Radiological terrorism and accidents have emerged as a real threat in the past few years
throughout the world. While methods exist to quantify the radiation exposure and the future cancer risk
in an exposed individual (i.e. the gold standard being cytogenetics), these methods are laborious, require
specific technical expertise, and are not applicable in a real life situation where thousands need to be
triaged. For this, rapid, accurate, and non-invasive methods need to be developed. We recently published
on the radiation signature in urine of total body irradiated patients. While statistically significant
differences were observed between pre- and post-exposure, the specificity of the signature was not
investigated. In a real life situation, where victims may present with underlying conditions or trauma, it is
important to be able to distinguish in a reliable way those that require further triage based on radiation
exposure. For this purpose urine samples from patients presenting with sepsis or trauma were
investigated through metabolomics. Global metabolomic profiling was obtained through analysis with
Ultra Performance Liquid Chromatography (UPLC) coupled to time-of-flight mass spectrometry (TOFMS)
(Waters). Peak alignment and deconvolution of the chromatographic data were conducted with
MarkerLynx software (Waters, MA). Prior to further analysis, each sample was normalized to its respective
creatinine. Statistical analysis was conducted through the software MetaboLyzer and putative identities
were assigned based on the metabolite databases HMDB, KEGG, Lipidmaps, and BioCyc. An increased
number of acylcarnitines were noted in the trauma samples, distinct from the ones previously identified
in radiation samples. In contrast, sepsis samples show an increase in excretion of putative L-carnitine, the
basic component of all acylcarnitines. In addition, sepsis samples exhibit an increase in a number of amino
acids and methyl conjugates of guanine and guanosine. Developing therefore a panel of metabolites that
334 | P a g e
