Plasma metabolomic signatures from patients following high-dose total body irradiation†

IF 3 4区 生物学 Q3 BIOCHEMISTRY & MOLECULAR BIOLOGY
Molecular omics Pub Date : 2023-03-28 DOI:10.1039/D2MO00274D
Xiedong Hong, Lang Tian, Qiong Wu, Liming Gu, Wenli Wang, Hanxu Wu, Mingxiao Zhao, Xiaojin Wu and Chang Wang
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引用次数: 1

Abstract

Despite some advances in the study of radiation injuries, effective methods of prevention and treatment of severe acute radiation syndrome or illness (ARS) are still lacking. Therefore, an in-depth understanding of the biological characteristics associated with high dose radiation is essential to reveal the mechanisms underlying the varied biological processes following high dose radiation and the development of novel potent radioprotective agents. In the present study, plasma metabolic characteristics were investigated using hematopoietic stem cell transplantation patients (n = 36) undergoing total body ionizing irradiation (TBI) utilizing gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS). Plasma was collected pre-irradiation, 3 days after completion of fractionated radiation therapy with a total dose of 12 Gy delivered at a dose rate of 8 cGy min−1. These metabolic disorders involve the dysregulation of the gut microflora, a shift in energy supply from aerobic respiration toward ketogenesis, protein synthesis and metabolism in response to TBI. Furthermore, the panel of four metabolic markers with most potential consisting of PC (O-38:5), urate, ornithine, and GCDCS for radiation injury was chosen by combining multiple methods of data processing that included univariate analysis, partial least squares discriminant analysis (PLS-DA), and multivariable stepwise linear regression analysis. While similar patterns of metabolic alterations were observed in patients of different genders, disease types and ages, specific changes were also found in specific patients following high doses of exposure. These findings provide valuable information for selecting metabolic biomarker panels for radiation injury, clues for radiation pathology and therapeutic interventions involved in high-dose radiation exposure.

Abstract Image

高剂量全身照射后患者血浆代谢组学特征
尽管辐射损伤的研究取得了一些进展,但严重急性辐射综合征或疾病(ARS)的有效预防和治疗方法仍然缺乏。因此,深入了解与高剂量辐射相关的生物学特性对于揭示高剂量辐射后各种生物学过程的潜在机制以及开发新型强效辐射防护剂至关重要。在本研究中,利用气相色谱-质谱法(GC-MS)和液相色谱-色谱-质谱仪(LC-MS),对接受全身电离辐射(TBI)的造血干细胞移植患者(n=36)的血浆代谢特征进行了研究。在完成分次放射治疗后3天,在放射前采集血浆,总剂量为12 Gy,剂量率为8 cGy min−1。这些代谢紊乱涉及肠道菌群的失调,能量供应从有氧呼吸向生酮、蛋白质合成和代谢的转变,以应对TBI。此外,通过结合多种数据处理方法,包括单变量分析、偏最小二乘判别分析(PLS-DA)和多变量逐步线性回归分析,选择了由PC(O-38:5)、尿酸盐、鸟氨酸和GCDCS组成的四种最有可能用于辐射损伤的代谢标志物。虽然在不同性别、疾病类型和年龄的患者中观察到类似的代谢变化模式,但在高剂量暴露后的特定患者中也发现了特定的变化。这些发现为选择辐射损伤的代谢生物标志物小组、辐射病理学线索和高剂量辐射暴露的治疗干预措施提供了有价值的信息。
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来源期刊
Molecular omics
Molecular omics Biochemistry, Genetics and Molecular Biology-Biochemistry
CiteScore
5.40
自引率
3.40%
发文量
91
期刊介绍: Molecular Omics publishes high-quality research from across the -omics sciences. Topics include, but are not limited to: -omics studies to gain mechanistic insight into biological processes – for example, determining the mode of action of a drug or the basis of a particular phenotype, such as drought tolerance -omics studies for clinical applications with validation, such as finding biomarkers for diagnostics or potential new drug targets -omics studies looking at the sub-cellular make-up of cells – for example, the subcellular localisation of certain proteins or post-translational modifications or new imaging techniques -studies presenting new methods and tools to support omics studies, including new spectroscopic/chromatographic techniques, chip-based/array technologies and new classification/data analysis techniques. New methods should be proven and demonstrate an advance in the field. Molecular Omics only accepts articles of high importance and interest that provide significant new insight into important chemical or biological problems. This could be fundamental research that significantly increases understanding or research that demonstrates clear functional benefits. Papers reporting new results that could be routinely predicted, do not show a significant improvement over known research, or are of interest only to the specialist in the area are not suitable for publication in Molecular Omics.
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