{"title":"基于干血斑代谢组学筛查新生儿先天性甲状腺功能减退症的代谢物生物标志物研究。","authors":"Xingyu Guo, Feng Suo, Yuting Wang, Di Yu, Yi Wang, Bulian Dong, Lingshan Gou, Xinhui Gan, Benjing Wang, Chaowen Yu, Xiaoxiang Xie, Dandan Linghu, Xinyu Liu, Maosheng Gu, Guowang Xu","doi":"10.1007/s00216-025-05828-w","DOIUrl":null,"url":null,"abstract":"<div><p>Congenital hypothyroidism (CH) can be detected early during thyroid-stimulating hormone (TSH) screening based on dried blood spot (DBS) samples. However, it falls short in differentiating between neonates with elevated TSH levels and those with CH, which leads to many neonates undergoing secondary diagnosis through venous blood sampling. Metabolomics was used to analyze metabolic alterations in neonates with CH, and identify DBS-based metabolite biomarkers for CH screening to reduce secondary diagnosis. Based on non-targeted metabolomics, the metabolic alterations in neonates with CH were analyzed in a discovery set and novel biomarkers were identified. The results of the discovery set revealed that the metabolic alterations in neonates with CH were primarily in amino acid and lipid metabolism, and identified novel metabolite biomarkers were thyroxine, 2-piperidinone, and PC (14:0/20:4). Then, these biomarkers were validated in a validation set, and the screening performance was still satisfactory. A rapid 3.5-min targeted method for three potential biomarkers was further developed and used to analyze a confirmation set. Analysis of the confirmation set re-validated the reliability of the biomarkers, and a biomarker combinational model equation and an appropriate cutoff value were defined. Each set of DBS samples included neonates with health, hyperthyrotropinemia, and CH. The novel metabolite biomarkers from DBS samples demonstrate significant potential for CH screening in neonates, effectively reducing the requirement associated with secondary diagnosis of mis-screened neonates.</p><h3>Graphical Abstract</h3>\n<div><figure><div><div><picture><source><img></source></picture></div></div></figure></div></div>","PeriodicalId":462,"journal":{"name":"Analytical and Bioanalytical Chemistry","volume":"417 13","pages":"2889 - 2902"},"PeriodicalIF":3.8000,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Metabolite biomarkers of screening neonatal congenital hypothyroidism based on dried blood spot metabolomics\",\"authors\":\"Xingyu Guo, Feng Suo, Yuting Wang, Di Yu, Yi Wang, Bulian Dong, Lingshan Gou, Xinhui Gan, Benjing Wang, Chaowen Yu, Xiaoxiang Xie, Dandan Linghu, Xinyu Liu, Maosheng Gu, Guowang Xu\",\"doi\":\"10.1007/s00216-025-05828-w\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Congenital hypothyroidism (CH) can be detected early during thyroid-stimulating hormone (TSH) screening based on dried blood spot (DBS) samples. However, it falls short in differentiating between neonates with elevated TSH levels and those with CH, which leads to many neonates undergoing secondary diagnosis through venous blood sampling. Metabolomics was used to analyze metabolic alterations in neonates with CH, and identify DBS-based metabolite biomarkers for CH screening to reduce secondary diagnosis. Based on non-targeted metabolomics, the metabolic alterations in neonates with CH were analyzed in a discovery set and novel biomarkers were identified. The results of the discovery set revealed that the metabolic alterations in neonates with CH were primarily in amino acid and lipid metabolism, and identified novel metabolite biomarkers were thyroxine, 2-piperidinone, and PC (14:0/20:4). Then, these biomarkers were validated in a validation set, and the screening performance was still satisfactory. A rapid 3.5-min targeted method for three potential biomarkers was further developed and used to analyze a confirmation set. Analysis of the confirmation set re-validated the reliability of the biomarkers, and a biomarker combinational model equation and an appropriate cutoff value were defined. Each set of DBS samples included neonates with health, hyperthyrotropinemia, and CH. The novel metabolite biomarkers from DBS samples demonstrate significant potential for CH screening in neonates, effectively reducing the requirement associated with secondary diagnosis of mis-screened neonates.</p><h3>Graphical Abstract</h3>\\n<div><figure><div><div><picture><source><img></source></picture></div></div></figure></div></div>\",\"PeriodicalId\":462,\"journal\":{\"name\":\"Analytical and Bioanalytical Chemistry\",\"volume\":\"417 13\",\"pages\":\"2889 - 2902\"},\"PeriodicalIF\":3.8000,\"publicationDate\":\"2025-03-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Analytical and Bioanalytical Chemistry\",\"FirstCategoryId\":\"92\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s00216-025-05828-w\",\"RegionNum\":2,\"RegionCategory\":\"化学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BIOCHEMICAL RESEARCH METHODS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Analytical and Bioanalytical Chemistry","FirstCategoryId":"92","ListUrlMain":"https://link.springer.com/article/10.1007/s00216-025-05828-w","RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
Metabolite biomarkers of screening neonatal congenital hypothyroidism based on dried blood spot metabolomics
Congenital hypothyroidism (CH) can be detected early during thyroid-stimulating hormone (TSH) screening based on dried blood spot (DBS) samples. However, it falls short in differentiating between neonates with elevated TSH levels and those with CH, which leads to many neonates undergoing secondary diagnosis through venous blood sampling. Metabolomics was used to analyze metabolic alterations in neonates with CH, and identify DBS-based metabolite biomarkers for CH screening to reduce secondary diagnosis. Based on non-targeted metabolomics, the metabolic alterations in neonates with CH were analyzed in a discovery set and novel biomarkers were identified. The results of the discovery set revealed that the metabolic alterations in neonates with CH were primarily in amino acid and lipid metabolism, and identified novel metabolite biomarkers were thyroxine, 2-piperidinone, and PC (14:0/20:4). Then, these biomarkers were validated in a validation set, and the screening performance was still satisfactory. A rapid 3.5-min targeted method for three potential biomarkers was further developed and used to analyze a confirmation set. Analysis of the confirmation set re-validated the reliability of the biomarkers, and a biomarker combinational model equation and an appropriate cutoff value were defined. Each set of DBS samples included neonates with health, hyperthyrotropinemia, and CH. The novel metabolite biomarkers from DBS samples demonstrate significant potential for CH screening in neonates, effectively reducing the requirement associated with secondary diagnosis of mis-screened neonates.
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Analytical and Bioanalytical Chemistry’s mission is the rapid publication of excellent and high-impact research articles on fundamental and applied topics of analytical and bioanalytical measurement science. Its scope is broad, and ranges from novel measurement platforms and their characterization to multidisciplinary approaches that effectively address important scientific problems. The Editors encourage submissions presenting innovative analytical research in concept, instrumentation, methods, and/or applications, including: mass spectrometry, spectroscopy, and electroanalysis; advanced separations; analytical strategies in “-omics” and imaging, bioanalysis, and sampling; miniaturized devices, medical diagnostics, sensors; analytical characterization of nano- and biomaterials; chemometrics and advanced data analysis.
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