6卷 第1期
Department of Pediatric Surgery, Shengjing Hospital of China Medical University, Shenyang, Liaoning, 110004, China
纸质出版：2026-03-30
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Yuan Wei & Xiaobing Tang. (2026). Metabolomics in Pediatric Digestive Diseases and Congenital Malformations. 生物医学大数据, 6(1), 45-48.
Wei Yuan,Tang Xiaobing.Metabolomics in Pediatric Digestive Diseases and Congenital Malformations[J].Biomedical Data Science,2026,06(01):45-48.
Yuan Wei & Xiaobing Tang. (2026). Metabolomics in Pediatric Digestive Diseases and Congenital Malformations. 生物医学大数据, 6(1), 45-48. DOI： 10.47297/wspbdsWSP2752-630510.20260601.
Wei Yuan,Tang Xiaobing.Metabolomics in Pediatric Digestive Diseases and Congenital Malformations[J].Biomedical Data Science,2026,06(01):45-48. DOI： 10.47297/wspbdsWSP2752-630510.20260601.
Metabolomics
an emerging technology for studying dynamic changes of small-molecule metabolites in organisms
can sensitively reflect pathophysiological status and holds significant value in early disease diagnosis and mechanistic research. This review summarizes the research progress of metabolomics applications in pediatric digestive system diseases and congenital malformations. The article first introduces the background of metabolomics
including mainstream analytical platforms such as nuclear magnetic resonance (NMR)
liquid chromatography-mass spectrometry (LC-MS)
and gas chromatography-mass spectrometry (GC-MS) and their characteristics
and elaborates on the key mechanisms involved in the occurrence and development of congenital malformations. The review focuses on metabolomics applications in five pediatric digestive diseases: esophageal atresia
biliary atresia
Hirschsprung disease
inflammatory bowel disease
and necrotizing enterocolitis. Studies have demonstrated that metabolomics technology can identify novel biomarkers and metabolic pathways
providing crucial evidence for early diagnosis
prognostic assessment
and therapeutic target development in pediatric digestive diseases. Finally
the article indicates that future metabolomics research should strengthen large-scale population validation and integrate multi-omics technologies with various biological samples for systematic analysis
thereby promoting clinical translation and application.
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