Transcriptional instability during evolving sepsis may limit biomarker based risk stratification.
<h4>Background</h4>Sepsis causes extensive morbidity and mortality in children worldwide. Prompt recognition and timely treatment of sepsis is critical in reducing morbidity and mortality. Genomic approaches are used to discover novel pathways, therapeutic targets and biomarkers. These m...
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Public Library of Science (PLoS)
2013-01-01
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| Series: | PLoS ONE |
| Online Access: | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0060501&type=printable |
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| author | Antonia Kwan Mike Hubank Asrar Rashid Nigel Klein Mark J Peters |
| author_facet | Antonia Kwan Mike Hubank Asrar Rashid Nigel Klein Mark J Peters |
| author_sort | Antonia Kwan |
| collection | DOAJ |
| description | <h4>Background</h4>Sepsis causes extensive morbidity and mortality in children worldwide. Prompt recognition and timely treatment of sepsis is critical in reducing morbidity and mortality. Genomic approaches are used to discover novel pathways, therapeutic targets and biomarkers. These may facilitate diagnosis and risk stratification to tailor treatment strategies.<h4>Objective</h4>To investigate the temporal gene expression during the evolution of sepsis induced multi-organ failure in response to a single organism, Neisseria meningitidis, in previously healthy children.<h4>Method</h4>RNA was extracted from serial blood samples (6 time points over 48 hours from presentation) from five critically ill children with meningococcal sepsis. Extracted RNA was hybridized to Affymetrix arrays. The RNA underwent strict quality control and standardized quantitation. Gene expression results were analyzed using GeneSpring software and Ingenuity Pathway Analysis.<h4>Result</h4>A marked variability in differential gene expression was observed between time points and between patients revealing dynamic expression changes during the evolution of sepsis. While there was evidence of time-dependent changes in expected gene networks including those involving immune responses and inflammatory pathways, temporal variation was also evident in specific "biomarkers" that have been proposed for diagnostic and risk stratification functions. The extent and nature of this variability was not readily explained by clinical phenotype.<h4>Conclusion</h4>This is the first study of its kind detailing extensive expression changes in children during the evolution of sepsis. This highlights a limitation of static or single time point biomarker estimation. Serial estimations or more comprehensive network approaches may be required to optimize risk stratification in complex, time-critical conditions such as evolving sepsis. |
| format | Article |
| id | doaj-art-6dad447bef1e4930b7e199dcffe1b365 |
| institution | Kabale University |
| issn | 1932-6203 |
| language | English |
| publishDate | 2013-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj-art-6dad447bef1e4930b7e199dcffe1b3652025-08-20T03:26:44ZengPublic Library of Science (PLoS)PLoS ONE1932-62032013-01-0183e6050110.1371/journal.pone.0060501Transcriptional instability during evolving sepsis may limit biomarker based risk stratification.Antonia KwanMike HubankAsrar RashidNigel KleinMark J Peters<h4>Background</h4>Sepsis causes extensive morbidity and mortality in children worldwide. Prompt recognition and timely treatment of sepsis is critical in reducing morbidity and mortality. Genomic approaches are used to discover novel pathways, therapeutic targets and biomarkers. These may facilitate diagnosis and risk stratification to tailor treatment strategies.<h4>Objective</h4>To investigate the temporal gene expression during the evolution of sepsis induced multi-organ failure in response to a single organism, Neisseria meningitidis, in previously healthy children.<h4>Method</h4>RNA was extracted from serial blood samples (6 time points over 48 hours from presentation) from five critically ill children with meningococcal sepsis. Extracted RNA was hybridized to Affymetrix arrays. The RNA underwent strict quality control and standardized quantitation. Gene expression results were analyzed using GeneSpring software and Ingenuity Pathway Analysis.<h4>Result</h4>A marked variability in differential gene expression was observed between time points and between patients revealing dynamic expression changes during the evolution of sepsis. While there was evidence of time-dependent changes in expected gene networks including those involving immune responses and inflammatory pathways, temporal variation was also evident in specific "biomarkers" that have been proposed for diagnostic and risk stratification functions. The extent and nature of this variability was not readily explained by clinical phenotype.<h4>Conclusion</h4>This is the first study of its kind detailing extensive expression changes in children during the evolution of sepsis. This highlights a limitation of static or single time point biomarker estimation. Serial estimations or more comprehensive network approaches may be required to optimize risk stratification in complex, time-critical conditions such as evolving sepsis.https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0060501&type=printable |
| spellingShingle | Antonia Kwan Mike Hubank Asrar Rashid Nigel Klein Mark J Peters Transcriptional instability during evolving sepsis may limit biomarker based risk stratification. PLoS ONE |
| title | Transcriptional instability during evolving sepsis may limit biomarker based risk stratification. |
| title_full | Transcriptional instability during evolving sepsis may limit biomarker based risk stratification. |
| title_fullStr | Transcriptional instability during evolving sepsis may limit biomarker based risk stratification. |
| title_full_unstemmed | Transcriptional instability during evolving sepsis may limit biomarker based risk stratification. |
| title_short | Transcriptional instability during evolving sepsis may limit biomarker based risk stratification. |
| title_sort | transcriptional instability during evolving sepsis may limit biomarker based risk stratification |
| url | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0060501&type=printable |
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