GNPS -Discovery of Noninvasive Biomarkers for Radiation Exposure via LC-MS-based Hair Metabolomics
Ontology highlight
ABSTRACT:
INSTRUMENT(S): Q Exactive
ORGANISM(S): Mus Musculus (ncbitaxon:10090)
SUBMITTER: 
Jiangjiang Zhu
PROVIDER: MSV000096086 | GNPS | Mon Oct 14 13:48:00 BST 2024
REPOSITORIES: GNPS
Similar Datasets
Project description:Ionizing radiation exposure from a potential nuclear energy plant leak or detonation of a nuclear weapon can cause massive casualties to both warfighters and civilians. Biomarkers in biological specimens like blood and tissue, such as RNA, proteins, and metabolites, have shown potential to determine radiation dose levels. However, these biomarkers in blood and urine are short-lived, typically detectable only within hours or a few days. To address the need for stable, long-term radiation exposure biomarkers, we developed two LC-MS-based methods using non-invasive hair samples to identify radiation-induced biomarkers
2024-10-14 | MSV000096086 | MassIVE
Project description:Abstract Purpose: There is a recognised need to develop new methods of high throughput, rapid and minimally invasive individual dose assessment for radiation exposure. The aim of this work is to establish a panel of highly radiation responsive genes suitable for biological dosimetry and to explore inter-individual variation in response to ionising radiation exposure.Materials and method: Analysis of gene expression in response to radiation was carried out using three independent techniques (microarray, Multiplex Quantitative RT-PCR and nCounter Analysis System) in human lymphocytes in culture and circulating blood exposed ex vivo from the same donors. Results: Variations in transcriptional response to exposure to ionising radiation analysed by microarray allowed the identification of genes which can be validated and measured accurately as biomarkers of radiation exposure using other techniques. We have identified genes which are consistently up-regulated following exposure at different time points to either 2 or 4 Gy of X-rays, for all individuals in blood and cultured lymphocytes. Most down-regulated genes including cyclins, centromeric and mitotic checkpoints proteins, particularly those associated with chromosome instability and cancer can only be detected in dividing cells. Conclusions: The data provides evidence that there are a number of genes which seem suitable for biological dosimetry, like SESN1, GADD45A, CDKN1A, CCNG1, FDXR, BBC3 and MDM2. ÊThese biomarkers could potentially be used for triage after large-scale radiological incidents. Variations in transcriptional response accurately measured by MQRT-PCRæ may allow the identification of biomarkers of radiation sensitivity and individual susceptibility and therefore being useful in radiation oncology.
2011-10-20 | E-TABM-1083 | biostudies-arrayexpress
Project description:Currently there is growing concern with respect to scenarios where people are likely to be presented with radiation exposure along with many kinds of other injuries such as trauma and infection. The potential for such scenarios was brought to reality with the events and aftermath of the Fukushima nuclear disaster in Japan. As such medical complications arising from such exposures would be poorly dealt with as no evidence-based guidelines exist for their rehabilitation or recovery. Our research intends to differentially characterize combined radiation and burn injuries and identify novel pathways and biomarkers. Such findings will lead to better medical practices in the diagnosis, care and rehabilitation of affected individuals. The study includes four groups of mice: 1) Control sham mice group (n=4), 2) Skin burn injury mice group (n=6), 3) Radiation injury mice group (n=6), 4) Combined radiation and burn injury mice group (n=6). We propose to characterize the effects of combined radiation and burn injuries using microRNA microarray analysis. Our primary aim is to identify novel molecular pathways and biomarkers specific to whole blood samples (serum) from mice exposed to combined radiation and burn injuries. B6D2F1/J female mice will be used. 30 days following combined radiation and burn injuries arterial blood will be harvested from euthanized mice. 200ul of serum from whole blood samples will be used for microRNA microarray experiments (Affymetrix).
2015-05-15 | E-GEOD-66739 | biostudies-arrayexpress
Project description:Identifying radiation exposure biomarkers from mouse blood transcriptome
| PRJNA149219 | ENA
Project description:The population's increasing risk of acute large-scale radiological/nuclear exposures underlines the need for functional radiation biomarkers. As ionizing radiation triggers a complex response on the genome, proteome, and metabolome level, all were already reported as suitable indicators of radiation-induced damage in vitro or in animal models. We aim to analyze the blood of total-body irradiated (TBI) leukaemia patients using a mass spectrometry approach and to identify and quantify plasma proteins before and after irradiation. Combining two independent mass spectrometry approaches we identified 15 plasma proteins differing in the blood of TBI patients before and after irradiation. The majority of proteins were associated with the inflammatory responce of the immune system and with metabolism of lipids. These candidate radiation biomarkers might have implications for practical biological dosimetry.
2024-06-16 | PXD043516 | Pride
Project description:Objective:Biomarkers of radiation injury are needed in planning therapeutic measures for cancer patients receiving radiation therapy and civilians exposed to nuclear events. Previous research has highlighted the impact of radiation damage, with cancer patients developing acute disorders including radiation induced pneumonitis or chronic disorders including pulmonary fibrosis months after radiation therapy ends. Discovery of biomarkers that predict these injuries will offer the potential to treat people proactively to mitigate this damage and improve quality of life. Recent research has highlighted the potential for messenger RNA (mRNA), microRNA (miRNA), and long non-coding RNA (lncRNA) to be used as radiation biomarkers. Our study focused on the changes in these RNAs at 48h after radiation exposure of mouse lung tissue to define biological pathway changes and determine potential biomarkers. Result: We observed sustained dysregulation of specific mRNAs, lncRNAs, and miRNAs across all doses. We observed gene dysregulation which can be used to develop both markers to identify no-exposure vs radiation exposure including Hba and Hbb mRNA which were dysregulated even at 1 Gy. We also observed genes which can indicate high dose exposure including Cpt1c and Pdk4. Gdf15, and Eda2r, mRNA markers of senescence and fibrosis, were the most significantly upregulated. Only three miRNAs were significantly dysregulated across all radiation doses, with miRNA-142-3p and miRNA-142-5p downregulated and miRNA-34a-5p upregulated. IPA analysis indicated that numerous pathways relevant to immune function, cell proliferation and survival decreased with increasing doses of radiation. This data highlighted early pathways of dysregulation depending on dose of exposure. This data will help with development of treatments and in medical decision-making. Further experiments are planned to develop medical countermeasures based on this early dysregulation.
2022-06-06 | GSE202586 | GEO
Project description:Early-onset preeclampsia (EOPE) is a severe pregnancy complication associated with significant maternal and fetal morbidity and mortality. Currently, there is a critical need for accurate, non-invasive biomarkers to facilitate early diagnosis and effective management of EOPE. In this study, we aimed to investigate the transcriptional alterations and non-invasive biomarker potential of peripheral blood microRNAs in patients with EOPE. Through our research, we successfully identified two reliable plasma miRNA biomarkers and proposed a circulating two-miRNA panel for the non-invasive early detection of EOPE. Additionally, we independently validated our findings in different patient cohorts using various technological platforms.
2023-06-14 | GSE234611 | GEO
Project description:Long non-coding RNAs (lncRNAs) are emerging as key molecules in regulating many biological processes and have been implicated in development and disease pathogenesis. Biomarkers of cancer and normal tissue response to treatment are of great interest in precision medicine and for public health and medical management of disasters such as assessing radiation injury following accidental or intentional exposure. Circulating and functional RNAs, including microRNAs (miRNAs) and lncRNAs, in whole blood and other body fluids represent potential valuable candidates as biomarkers. Early prediction of possible acute, intermediate, and delayed effects of radiation exposure will enable timely therapeutic interventions. To address whether lncRNAs could serve as biomarkers for radiation bio-dosimetry, we performed whole genome transcriptome analysis in a mouse model after whole body irradiation. Differential lncRNA expression patterns were evaluated at 16-, 24-, and 48-hour time points post irradiation in total RNA isolated from whole blood of mice exposed to 1, 2, 4, 8, and 12 Gy of gamma-rays. Sham irradiated animals served as controls. Significant alterations in the expression patterns of lncRNAs were observed after different radiation doses at the various timepoints. We identified several lncRNAs known for DNA damage response as well as immune response as radiation induced biomarkers. Long non-coding RNA targets of tumor protein 53 (P53), Trp53cor1, Dino, Pvt1 and Tug1 and an upstream regulator of p53, Meg3 were altered in response to radiation. Gm14005 (Morrbid) and Tmevpg1 were regulated by radiation across all time points and doses. These two lncRNAs have important potential as blood based radiation biomarkers; Gm14005 (Morrbid) has recently been shown to play a key role in inflammatory response while Tmevpg1 has been implicated in the regulation of interferon-gamma. Precise molecular biomarkers will not only enable the development and effective use of medical countermeasures but also may be used to detect and circumvent or mitigate normal tissue injury in cancer radiotherapy treatments.
2018-05-31 | GSE104121 | GEO
Project description:One of the most likely risks astronauts on long duration space missions face is exposure to ionizing radiation associated with highly energetic and charged heavy (HZE) particles. Since access to medical expertise on such a mission is limited at best, early diagnosis and mitigation of such exposure is critical. In order to accurately determine the dosage within 1 hour post-exposure, dose-dependent âbiomarkersâ are needed. Therefore, we performed a dose-course transcriptional analysis for radiation exposure at 0, 0.3, 1.5, and 3.0 Gy with corresponding time point at 1 hour (hr) post-exposure using Affymetrix® GeneChip® Human Gene 1.0 ST v1 Array chips. The analysis of our data suggests a set of sensitive genetic biomarkers specific to each radiation level as well as generic radiation response biomarkers. Upregulated biomarkers can then be used within lab-on-a-chip (LOC) systems to detect exposure to ionizing radiation. A total of sixteen human samples representing radiation exposure at levels 0 Gy, 0.3 Gy, 1.5 Gy and 3.0 Gy at time point 1 hour (hr) post-exposure were constructed. Blood samples were extracted from four human volunteers, and were irradiated. Leukocytes were extracted, and gene expression was measured. Samples for all four volunteers were measured at 1 hr for all four dose levels, resulting in four replicates at each dose level. Thus, a total of 4 samples at each of the four radiation levels were sampled, yielding the total of 16 samples.
2016-07-03 | E-GEOD-64375 | biostudies-arrayexpress
Project description:Purpose: There is a need for point-of-care diagnostics for future mass casualty events involving radiation exposure. The development of radiation exposure and dose prediction algorithms for biodosimetry is needed for screening of large populations during these scenarios, and exploration of the potential effects which sex, age, genetic heterogeneity, and physiological comorbidities may have on the utility of biodosimetry diagnostics is needed. In the current study, proteomic profiling was used to examine sex specific differences in age matched C57BL6 mice on the blood proteome following radiation exposure and the usefulness of development and application of biodosimetry algorithms using both male and female samples. Methods: C57BL6 male and female mice between 9-11 weeks of age received a single total body radiation exposure of either 2, 4 or 8 Gy with plasma collection at days 1, 3 and 7 post-irradiation. Plasma was then screened using the SomaScan v4.1 assay for ~7000 protein analytes. A subset panel of protein biomarkers demonstrated significant (FDR<0.05 and |logFC|>0.2) changes in expression following radiation exposure. All proteins were used for feature selection to build predictive models of radiation exposure using different sample and sex specific cohorts. Both binary (prediction of any radiation exposure) and multidose (prediction of specific radiation dose) model series were developed using either female and male samples combined or only female or only male samples. The binary series (Models 1, 2 and 3) and multidose series (Models 4, 5 and 6) series included female/male combined, female only and male only respectively. Results: Detectable values were obtained for all ~7000 proteins included in the SomaScan assay for all samples. Each model algorithm built using a unique sample cohort was validated with a training set of samples and tested with a separate new sample series. Overall predictive accuracies in the binary model series was ~100% at the model training level and when tested with fresh samples 97.9% for Model 1(Female and Male) and 100% for Model 2 (Female only) and Model 3 (Male only). When sex specific Models’ 2 and 3 were tested with the opposite sex, the overall predictive accuracy rate dropped to 62.5% for Model 2 and remained 100% for Model 3. The overall predictive accuracy rate in the multidose model series was 100% for all models at the model training level and when tested with fresh samples 83.3%, 75% and 83.3% for Multidose Models 4-6 respectively. When sex specific Models’ 5 (Female only) and Model 6 (Male only) were tested with the opposite sex the overall predictive accuracy rate dropped to 52.1% and 68.8% respectively. Conclusion: These models represent novel predictive panels of radiation responsive proteomic biomarkers and illustrate the utility and necessity of considering sex specific differences in development of radiation biodosimetry prediction algorithms. As sex specific differences were observed in this study, and as use of point-of-care radiation diagnostics in future mass casualty settings will necessarily include persons of both sexes, consideration of sex specific variation is essential to ensure these diagnostic tools have practical utility in the field.
2024-05-11 | GSE267131 | GEO