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Identification of new biomarkers and immune infiltration characteristics of sepsis in very low birth weight infants
Sepsis is a life-threatening condition, especially in very low birth weight (VLBW) infants, and its pathogenesis remains unclear. Effective biomarkers need to be found to diagnose and treat the disease at an early stage. The Gene Expression Omnibus (GEO) database was screened and analyzed for differ...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Association of Basic Medical Sciences of Federation of Bosnia and Herzegovina
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10494841/ https://www.ncbi.nlm.nih.gov/pubmed/37139640 http://dx.doi.org/10.17305/bb.2023.8966 |
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author | Luo, Yujia Jiang, Zhou Gu, Rui Zhang, Xuandong Wei, Li Zhou, Yuanyuan Zhang, Songying |
author_facet | Luo, Yujia Jiang, Zhou Gu, Rui Zhang, Xuandong Wei, Li Zhou, Yuanyuan Zhang, Songying |
author_sort | Luo, Yujia |
collection | PubMed |
description | Sepsis is a life-threatening condition, especially in very low birth weight (VLBW) infants, and its pathogenesis remains unclear. Effective biomarkers need to be found to diagnose and treat the disease at an early stage. The Gene Expression Omnibus (GEO) database was screened and analyzed for differentially expressed genes (DEGs) in VLBW infants with sepsis. DEGs were then analyzed for functional enrichment. A weighted gene co-expression network analysis (WGCNA) was performed to identify the key modules and genes. The optimal feature genes (OFGs) were created using three machine learning algorithms. The single-sample Gene Set Enrichment Analysis (ssGSEA) scored the degree of immune cell enrichment between septic and control patients, and the correlation between OFGs and immune cells was evaluated. A total of 101 DEGs were identified between the sepsis and control samples. DEGs were mainly associated with immune responses and inflammatory signaling pathways in the enrichment analysis. In the WGCNA analysis, the MEturquoise module was significantly correlated with sepsis in VLBW infants (cor ═ 0.57, P < 0.001). By intersecting OFGs derived from three machine learning algorithms, two biomarkers were identified: glycogenin 1 (GYG1) and resistin (RETN). The area under the curves of GYG1 and RETN was greater than 0.97 in the testing set. The ssGSEA indicated immune cells infiltration in septic VLBW infants, and GYG1 and RETN revealed close correlations with immune cells. New biomarkers offer promising insights into the diagnosis and treatment of sepsis in VLBW infants. |
format | Online Article Text |
id | pubmed-10494841 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Association of Basic Medical Sciences of Federation of Bosnia and Herzegovina |
record_format | MEDLINE/PubMed |
spelling | pubmed-104948412023-10-01 Identification of new biomarkers and immune infiltration characteristics of sepsis in very low birth weight infants Luo, Yujia Jiang, Zhou Gu, Rui Zhang, Xuandong Wei, Li Zhou, Yuanyuan Zhang, Songying Biomol Biomed Research Article Sepsis is a life-threatening condition, especially in very low birth weight (VLBW) infants, and its pathogenesis remains unclear. Effective biomarkers need to be found to diagnose and treat the disease at an early stage. The Gene Expression Omnibus (GEO) database was screened and analyzed for differentially expressed genes (DEGs) in VLBW infants with sepsis. DEGs were then analyzed for functional enrichment. A weighted gene co-expression network analysis (WGCNA) was performed to identify the key modules and genes. The optimal feature genes (OFGs) were created using three machine learning algorithms. The single-sample Gene Set Enrichment Analysis (ssGSEA) scored the degree of immune cell enrichment between septic and control patients, and the correlation between OFGs and immune cells was evaluated. A total of 101 DEGs were identified between the sepsis and control samples. DEGs were mainly associated with immune responses and inflammatory signaling pathways in the enrichment analysis. In the WGCNA analysis, the MEturquoise module was significantly correlated with sepsis in VLBW infants (cor ═ 0.57, P < 0.001). By intersecting OFGs derived from three machine learning algorithms, two biomarkers were identified: glycogenin 1 (GYG1) and resistin (RETN). The area under the curves of GYG1 and RETN was greater than 0.97 in the testing set. The ssGSEA indicated immune cells infiltration in septic VLBW infants, and GYG1 and RETN revealed close correlations with immune cells. New biomarkers offer promising insights into the diagnosis and treatment of sepsis in VLBW infants. Association of Basic Medical Sciences of Federation of Bosnia and Herzegovina 2023-10-01 2023-10-01 /pmc/articles/PMC10494841/ /pubmed/37139640 http://dx.doi.org/10.17305/bb.2023.8966 Text en © 2023 Luo et al. https://creativecommons.org/licenses/by/4.0/This article is available under a Creative Commons License (Attribution 4.0 International, as described at https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Research Article Luo, Yujia Jiang, Zhou Gu, Rui Zhang, Xuandong Wei, Li Zhou, Yuanyuan Zhang, Songying Identification of new biomarkers and immune infiltration characteristics of sepsis in very low birth weight infants |
title | Identification of new biomarkers and immune infiltration characteristics of sepsis in very low birth weight infants |
title_full | Identification of new biomarkers and immune infiltration characteristics of sepsis in very low birth weight infants |
title_fullStr | Identification of new biomarkers and immune infiltration characteristics of sepsis in very low birth weight infants |
title_full_unstemmed | Identification of new biomarkers and immune infiltration characteristics of sepsis in very low birth weight infants |
title_short | Identification of new biomarkers and immune infiltration characteristics of sepsis in very low birth weight infants |
title_sort | identification of new biomarkers and immune infiltration characteristics of sepsis in very low birth weight infants |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10494841/ https://www.ncbi.nlm.nih.gov/pubmed/37139640 http://dx.doi.org/10.17305/bb.2023.8966 |
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