Juyoung Lee, Byeong-Gon Ji, Eun-Jung Hong, Jae-Pil Jeon
{"title":"血清代谢物与生物库血清样本的血清指标和分析前因素的关系","authors":"Juyoung Lee, Byeong-Gon Ji, Eun-Jung Hong, Jae-Pil Jeon","doi":"10.1089/bio.2023.0130","DOIUrl":null,"url":null,"abstract":"<p><p><b><i>Background:</i></b> Serum indices (hemolysis, icterus, and lipemia; HIL) are known to impact clinical chemistry assay results. This study aimed to investigate the impact of HIL indices on serum metabolite profiles and the association of serum metabolite levels with pre-analytical factors of serum samples. <b><i>Methods:</i></b> A cohort of serum samples (<i>n</i> = 12,196) from the Korean Genome and Epidemiology Study (KoGES) was analyzed for HIL indices and the pre-analytical variables (SPRECs) which were generated in the process of serum collection. We further performed targeted metabolomics on a subset comprising hemolyzed (<i>n</i> = 60), icteric (<i>n</i> = 60), lipemic (<i>n</i> = 60) groups, and a common control group of non-HIL samples (<i>n</i> = 60) using the Absolute IDQ p180 kit. <b><i>Results:</i></b> We found 22 clinical chemistry analytes significantly associated with hemolysis, 25 with icterus, and 24 with lipemia (<i>p</i> < 0.0001). Serum metabolites (<i>n</i> = 27) were associated with all of hemolysis, icterus, and lipemia (<i>p</i> < 0.05). The PC ae C36 2 had exhibited a significant association with pre-analytical factors corresponding to the third (pre-centrifugation delay between processing) and sixth (post-centrifugation) elements of the SPREC. <b><i>Conclusions:</i></b> This study showed the association of the serum index and pre-analytical factors with serum metabolite profiles. In addition, the association of pre-analytical factors with serum metabolite concentrations would corroborate the utility of SPRECs for the quality control of biobanked serum samples.</p>","PeriodicalId":55358,"journal":{"name":"Biopreservation and Biobanking","volume":" ","pages":""},"PeriodicalIF":1.6000,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Association of Serum Metabolites with Serum Indices and Preanalytical Factors of Biobanked Serum Samples.\",\"authors\":\"Juyoung Lee, Byeong-Gon Ji, Eun-Jung Hong, Jae-Pil Jeon\",\"doi\":\"10.1089/bio.2023.0130\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p><b><i>Background:</i></b> Serum indices (hemolysis, icterus, and lipemia; HIL) are known to impact clinical chemistry assay results. This study aimed to investigate the impact of HIL indices on serum metabolite profiles and the association of serum metabolite levels with pre-analytical factors of serum samples. <b><i>Methods:</i></b> A cohort of serum samples (<i>n</i> = 12,196) from the Korean Genome and Epidemiology Study (KoGES) was analyzed for HIL indices and the pre-analytical variables (SPRECs) which were generated in the process of serum collection. We further performed targeted metabolomics on a subset comprising hemolyzed (<i>n</i> = 60), icteric (<i>n</i> = 60), lipemic (<i>n</i> = 60) groups, and a common control group of non-HIL samples (<i>n</i> = 60) using the Absolute IDQ p180 kit. <b><i>Results:</i></b> We found 22 clinical chemistry analytes significantly associated with hemolysis, 25 with icterus, and 24 with lipemia (<i>p</i> < 0.0001). Serum metabolites (<i>n</i> = 27) were associated with all of hemolysis, icterus, and lipemia (<i>p</i> < 0.05). The PC ae C36 2 had exhibited a significant association with pre-analytical factors corresponding to the third (pre-centrifugation delay between processing) and sixth (post-centrifugation) elements of the SPREC. <b><i>Conclusions:</i></b> This study showed the association of the serum index and pre-analytical factors with serum metabolite profiles. In addition, the association of pre-analytical factors with serum metabolite concentrations would corroborate the utility of SPRECs for the quality control of biobanked serum samples.</p>\",\"PeriodicalId\":55358,\"journal\":{\"name\":\"Biopreservation and Biobanking\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":1.6000,\"publicationDate\":\"2024-07-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Biopreservation and Biobanking\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1089/bio.2023.0130\",\"RegionNum\":4,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biopreservation and Biobanking","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1089/bio.2023.0130","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Association of Serum Metabolites with Serum Indices and Preanalytical Factors of Biobanked Serum Samples.
Background: Serum indices (hemolysis, icterus, and lipemia; HIL) are known to impact clinical chemistry assay results. This study aimed to investigate the impact of HIL indices on serum metabolite profiles and the association of serum metabolite levels with pre-analytical factors of serum samples. Methods: A cohort of serum samples (n = 12,196) from the Korean Genome and Epidemiology Study (KoGES) was analyzed for HIL indices and the pre-analytical variables (SPRECs) which were generated in the process of serum collection. We further performed targeted metabolomics on a subset comprising hemolyzed (n = 60), icteric (n = 60), lipemic (n = 60) groups, and a common control group of non-HIL samples (n = 60) using the Absolute IDQ p180 kit. Results: We found 22 clinical chemistry analytes significantly associated with hemolysis, 25 with icterus, and 24 with lipemia (p < 0.0001). Serum metabolites (n = 27) were associated with all of hemolysis, icterus, and lipemia (p < 0.05). The PC ae C36 2 had exhibited a significant association with pre-analytical factors corresponding to the third (pre-centrifugation delay between processing) and sixth (post-centrifugation) elements of the SPREC. Conclusions: This study showed the association of the serum index and pre-analytical factors with serum metabolite profiles. In addition, the association of pre-analytical factors with serum metabolite concentrations would corroborate the utility of SPRECs for the quality control of biobanked serum samples.
Biopreservation and BiobankingBiochemistry, Genetics and Molecular Biology-General Biochemistry,Genetics and Molecular Biology
自引率
12.50%
发文量
114
期刊介绍:
Biopreservation and Biobanking is the first journal to provide a unifying forum for the peer-reviewed communication of recent advances in the emerging and evolving field of biospecimen procurement, processing, preservation and banking, distribution, and use. The Journal publishes a range of original articles focusing on current challenges and problems in biopreservation, and advances in methods to address these issues related to the processing of macromolecules, cells, and tissues for research.
In a new section dedicated to Emerging Markets and Technologies, the Journal highlights the emergence of new markets and technologies that are either adopting or disrupting the biobank framework as they imprint on society. The solutions presented here are anticipated to help drive innovation within the biobank community.
Biopreservation and Biobanking also explores the ethical, legal, and societal considerations surrounding biobanking and biorepository operation. Ideas and practical solutions relevant to improved quality, efficiency, and sustainability of repositories, and relating to their management, operation and oversight are discussed as well.