Ilona den Hartog, Laura B Zwep, Jacqueline J Meulman, Thomas Hankemeier, Ewoudt M W van de Garde, J G Coen van Hasselt
{"title":"肺炎链球菌相关社区获得性肺炎的纵向代谢物分析。","authors":"Ilona den Hartog, Laura B Zwep, Jacqueline J Meulman, Thomas Hankemeier, Ewoudt M W van de Garde, J G Coen van Hasselt","doi":"10.1007/s11306-024-02091-5","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>Longitudinal biomarkers in patients with community-acquired pneumonia (CAP) may help in monitoring of disease progression and treatment response. The metabolic host response could be a potential source of such biomarkers since it closely associates with the current health status of the patient.</p><p><strong>Objectives: </strong>In this study we performed longitudinal metabolite profiling in patients with CAP for a comprehensive range of metabolites to identify potential host response biomarkers.</p><p><strong>Methods: </strong>Previously collected serum samples from CAP patients with confirmed Streptococcus pneumoniae infection (n = 25) were used. Samples were collected at multiple time points, up to 30 days after admission. A wide range of metabolites was measured, including amines, acylcarnitines, organic acids, and lipids. The associations between metabolites and C-reactive protein (CRP), procalcitonin, CURB disease severity score at admission, and total length of stay were evaluated.</p><p><strong>Results: </strong>Distinct longitudinal profiles of metabolite profiles were identified, including cholesteryl esters, diacyl-phosphatidylethanolamine, diacylglycerols, lysophosphatidylcholines, sphingomyelin, and triglycerides. Positive correlations were found between CRP and phosphatidylcholine (34:1) (cor = 0.63) and negative correlations were found for CRP and nine lysophosphocholines (cor = - 0.57 to - 0.74). The CURB disease severity score was negatively associated with six metabolites, including acylcarnitines (tau = - 0.64 to - 0.58). Negative correlations were found between the length of stay and six triglycerides (TGs), especially TGs (60:3) and (58:2) (cor = - 0.63 and - 0.61).</p><p><strong>Conclusion: </strong>The identified metabolites may provide insight into biological mechanisms underlying disease severity and may be of interest for exploration as potential treatment response monitoring biomarker.</p>","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":null,"pages":null},"PeriodicalIF":3.5000,"publicationDate":"2024-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10914916/pdf/","citationCount":"0","resultStr":"{\"title\":\"Longitudinal metabolite profiling of Streptococcus pneumoniae-associated community-acquired pneumonia.\",\"authors\":\"Ilona den Hartog, Laura B Zwep, Jacqueline J Meulman, Thomas Hankemeier, Ewoudt M W van de Garde, J G Coen van Hasselt\",\"doi\":\"10.1007/s11306-024-02091-5\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Introduction: </strong>Longitudinal biomarkers in patients with community-acquired pneumonia (CAP) may help in monitoring of disease progression and treatment response. The metabolic host response could be a potential source of such biomarkers since it closely associates with the current health status of the patient.</p><p><strong>Objectives: </strong>In this study we performed longitudinal metabolite profiling in patients with CAP for a comprehensive range of metabolites to identify potential host response biomarkers.</p><p><strong>Methods: </strong>Previously collected serum samples from CAP patients with confirmed Streptococcus pneumoniae infection (n = 25) were used. Samples were collected at multiple time points, up to 30 days after admission. A wide range of metabolites was measured, including amines, acylcarnitines, organic acids, and lipids. The associations between metabolites and C-reactive protein (CRP), procalcitonin, CURB disease severity score at admission, and total length of stay were evaluated.</p><p><strong>Results: </strong>Distinct longitudinal profiles of metabolite profiles were identified, including cholesteryl esters, diacyl-phosphatidylethanolamine, diacylglycerols, lysophosphatidylcholines, sphingomyelin, and triglycerides. Positive correlations were found between CRP and phosphatidylcholine (34:1) (cor = 0.63) and negative correlations were found for CRP and nine lysophosphocholines (cor = - 0.57 to - 0.74). The CURB disease severity score was negatively associated with six metabolites, including acylcarnitines (tau = - 0.64 to - 0.58). Negative correlations were found between the length of stay and six triglycerides (TGs), especially TGs (60:3) and (58:2) (cor = - 0.63 and - 0.61).</p><p><strong>Conclusion: </strong>The identified metabolites may provide insight into biological mechanisms underlying disease severity and may be of interest for exploration as potential treatment response monitoring biomarker.</p>\",\"PeriodicalId\":18506,\"journal\":{\"name\":\"Metabolomics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.5000,\"publicationDate\":\"2024-03-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10914916/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Metabolomics\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1007/s11306-024-02091-5\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENDOCRINOLOGY & METABOLISM\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Metabolomics","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s11306-024-02091-5","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENDOCRINOLOGY & METABOLISM","Score":null,"Total":0}
Longitudinal metabolite profiling of Streptococcus pneumoniae-associated community-acquired pneumonia.
Introduction: Longitudinal biomarkers in patients with community-acquired pneumonia (CAP) may help in monitoring of disease progression and treatment response. The metabolic host response could be a potential source of such biomarkers since it closely associates with the current health status of the patient.
Objectives: In this study we performed longitudinal metabolite profiling in patients with CAP for a comprehensive range of metabolites to identify potential host response biomarkers.
Methods: Previously collected serum samples from CAP patients with confirmed Streptococcus pneumoniae infection (n = 25) were used. Samples were collected at multiple time points, up to 30 days after admission. A wide range of metabolites was measured, including amines, acylcarnitines, organic acids, and lipids. The associations between metabolites and C-reactive protein (CRP), procalcitonin, CURB disease severity score at admission, and total length of stay were evaluated.
Results: Distinct longitudinal profiles of metabolite profiles were identified, including cholesteryl esters, diacyl-phosphatidylethanolamine, diacylglycerols, lysophosphatidylcholines, sphingomyelin, and triglycerides. Positive correlations were found between CRP and phosphatidylcholine (34:1) (cor = 0.63) and negative correlations were found for CRP and nine lysophosphocholines (cor = - 0.57 to - 0.74). The CURB disease severity score was negatively associated with six metabolites, including acylcarnitines (tau = - 0.64 to - 0.58). Negative correlations were found between the length of stay and six triglycerides (TGs), especially TGs (60:3) and (58:2) (cor = - 0.63 and - 0.61).
Conclusion: The identified metabolites may provide insight into biological mechanisms underlying disease severity and may be of interest for exploration as potential treatment response monitoring biomarker.
期刊介绍:
Metabolomics publishes current research regarding the development of technology platforms for metabolomics. This includes, but is not limited to:
metabolomic applications within man, including pre-clinical and clinical
pharmacometabolomics for precision medicine
metabolic profiling and fingerprinting
metabolite target analysis
metabolomic applications within animals, plants and microbes
transcriptomics and proteomics in systems biology
Metabolomics is an indispensable platform for researchers using new post-genomics approaches, to discover networks and interactions between metabolites, pharmaceuticals, SNPs, proteins and more. Its articles go beyond the genome and metabolome, by including original clinical study material together with big data from new emerging technologies.