Predicting acute lung injury in infants with congenital heart disease after cardiopulmonary bypass by gut microbiota
BackgroundAcute lung injury (ALI) is a serious and common complication that occurs in children with congenital heart disease after cardiopulmonary bypass (CPB) surgery, leading to higher mortality rates and poorer prognosis. Currently, there is no reliable predictive strategy for CPB-associated lung...
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Frontiers Media S.A.
2024-10-01
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| Series: | Frontiers in Immunology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fimmu.2024.1362040/full |
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| author | Lan Jiang Yueshuang Cun Qiang Wang Kede Wu Menglong Hu Zhen Wu Tianyi Zhu Zhaocong Yang Nishant Patel Nishant Patel Xinyu Cai Xinyu Cai Jirong Qi Xuming Mo |
| author_facet | Lan Jiang Yueshuang Cun Qiang Wang Kede Wu Menglong Hu Zhen Wu Tianyi Zhu Zhaocong Yang Nishant Patel Nishant Patel Xinyu Cai Xinyu Cai Jirong Qi Xuming Mo |
| author_sort | Lan Jiang |
| collection | DOAJ |
| description | BackgroundAcute lung injury (ALI) is a serious and common complication that occurs in children with congenital heart disease after cardiopulmonary bypass (CPB) surgery, leading to higher mortality rates and poorer prognosis. Currently, there is no reliable predictive strategy for CPB-associated lung injury (CPB-ALI) in infants. Certain characteristics of the gut microbiota could potentially serve as biomarkers for predicting the development of CPB-ALI.MethodsWe conducted 16S rRNA sequencing to analyze the characteristics of the intestinal microbiota in healthy controls and infants with CHD admitted to the hospital. The CHD infants were divided into CPB-ALI and non-ALI (CPB-NALI) groups based on postoperative outcomes. Bacterial functional pathway prediction analysis was performed using PIRCUSt2, and the gut microbiota composition associated with immune status was determined with heatmap. Random forest regression models and ROC curves were utilized to predict the occurrence of CPB-ALI.ResultsOur study revealed significantly different microbiota compositions among three groups (CON, CPB-ALI, and CPB-NALI). The microbiota diversity was low in the CPB-ALI group with high pathogen abundance and significant decrease in Bacteroides, while the opposite was observed in the CPB-NALI group. The microbiota dysbiosis index was high in the CPB-ALI group, with its dominant microbiota significantly associated with multiple metabolic pathways. Additionally, CPB-ALI patients showed high levels of inflammatory cytokines IL-8 and HMGB1 in their serum, with high expression of IL-8 being associated with Enterobacteriaceae. Further correlation analysis showed that the differences in gut bacterial taxonomy were related to the occurrence of ALI, length of stay in the cardiac care unit, and ventilation time. It is noteworthy that Escherichia Shigella performed best in distinguishing CPB-ALI patients from non-ALI patients.ConclusionsOur study suggests that postoperative ALI patients have distinct gut microbiota upon admission compared to non-ALI patients after surgery. Dysbiosis of the gut microbiota may potentially impact the progression of ALI through metabolic pathways, quorum sensing, and the levels of inflammatory factors expressed in the serum. Escherichia Shigella represents a potential predictive factor for the occurrence of ALI in CHD infants after surgery. Acute lung injury, congenital heart disease, cardiopulmonary bypass surgery, gut microbiota, biomarker |
| format | Article |
| id | doaj-art-0ea7ad6452594884aebd11768ed2c1e6 |
| institution | OA Journals |
| issn | 1664-3224 |
| language | English |
| publishDate | 2024-10-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Immunology |
| spelling | doaj-art-0ea7ad6452594884aebd11768ed2c1e62025-08-20T01:54:25ZengFrontiers Media S.A.Frontiers in Immunology1664-32242024-10-011510.3389/fimmu.2024.13620401362040Predicting acute lung injury in infants with congenital heart disease after cardiopulmonary bypass by gut microbiotaLan Jiang0Yueshuang Cun1Qiang Wang2Kede Wu3Menglong Hu4Zhen Wu5Tianyi Zhu6Zhaocong Yang7Nishant Patel8Nishant Patel9Xinyu Cai10Xinyu Cai11Jirong Qi12Xuming Mo13Department of Cardiothoracic Surgery, Children’s Hospital of Nanjing Medical University, Nanjing, ChinaDepartment of Cardiothoracic Surgery, Children’s Hospital of Nanjing Medical University, Nanjing, ChinaDepartment of Cardiothoracic Surgery, Children’s Hospital of Nanjing Medical University, Nanjing, ChinaDepartment of Cardiothoracic Surgery, Children’s Hospital of Nanjing Medical University, Nanjing, ChinaDepartment of Cardiothoracic Surgery, Children’s Hospital of Nanjing Medical University, Nanjing, ChinaDepartment of Cardiothoracic Surgery, Children’s Hospital of Nanjing Medical University, Nanjing, ChinaDepartment of Cardiothoracic Surgery, Children’s Hospital of Nanjing Medical University, Nanjing, ChinaDepartment of Cardiothoracic Surgery, Children’s Hospital of Nanjing Medical University, Nanjing, ChinaDepartment of Cardiothoracic Surgery, Children’s Hospital of Nanjing Medical University, Nanjing, ChinaSchool of Public Health, Nanjing Medical University, Nanjing, ChinaDepartment of Cardiothoracic Surgery, Children’s Hospital of Nanjing Medical University, Nanjing, ChinaSchool of Public Health, Nanjing Medical University, Nanjing, ChinaDepartment of Cardiothoracic Surgery, Children’s Hospital of Nanjing Medical University, Nanjing, ChinaDepartment of Cardiothoracic Surgery, Children’s Hospital of Nanjing Medical University, Nanjing, ChinaBackgroundAcute lung injury (ALI) is a serious and common complication that occurs in children with congenital heart disease after cardiopulmonary bypass (CPB) surgery, leading to higher mortality rates and poorer prognosis. Currently, there is no reliable predictive strategy for CPB-associated lung injury (CPB-ALI) in infants. Certain characteristics of the gut microbiota could potentially serve as biomarkers for predicting the development of CPB-ALI.MethodsWe conducted 16S rRNA sequencing to analyze the characteristics of the intestinal microbiota in healthy controls and infants with CHD admitted to the hospital. The CHD infants were divided into CPB-ALI and non-ALI (CPB-NALI) groups based on postoperative outcomes. Bacterial functional pathway prediction analysis was performed using PIRCUSt2, and the gut microbiota composition associated with immune status was determined with heatmap. Random forest regression models and ROC curves were utilized to predict the occurrence of CPB-ALI.ResultsOur study revealed significantly different microbiota compositions among three groups (CON, CPB-ALI, and CPB-NALI). The microbiota diversity was low in the CPB-ALI group with high pathogen abundance and significant decrease in Bacteroides, while the opposite was observed in the CPB-NALI group. The microbiota dysbiosis index was high in the CPB-ALI group, with its dominant microbiota significantly associated with multiple metabolic pathways. Additionally, CPB-ALI patients showed high levels of inflammatory cytokines IL-8 and HMGB1 in their serum, with high expression of IL-8 being associated with Enterobacteriaceae. Further correlation analysis showed that the differences in gut bacterial taxonomy were related to the occurrence of ALI, length of stay in the cardiac care unit, and ventilation time. It is noteworthy that Escherichia Shigella performed best in distinguishing CPB-ALI patients from non-ALI patients.ConclusionsOur study suggests that postoperative ALI patients have distinct gut microbiota upon admission compared to non-ALI patients after surgery. Dysbiosis of the gut microbiota may potentially impact the progression of ALI through metabolic pathways, quorum sensing, and the levels of inflammatory factors expressed in the serum. Escherichia Shigella represents a potential predictive factor for the occurrence of ALI in CHD infants after surgery. Acute lung injury, congenital heart disease, cardiopulmonary bypass surgery, gut microbiota, biomarkerhttps://www.frontiersin.org/articles/10.3389/fimmu.2024.1362040/fullacute lung injurycongenital heart diseasecardiopulmonary bypass surgerygut microbiotabiomarker |
| spellingShingle | Lan Jiang Yueshuang Cun Qiang Wang Kede Wu Menglong Hu Zhen Wu Tianyi Zhu Zhaocong Yang Nishant Patel Nishant Patel Xinyu Cai Xinyu Cai Jirong Qi Xuming Mo Predicting acute lung injury in infants with congenital heart disease after cardiopulmonary bypass by gut microbiota Frontiers in Immunology acute lung injury congenital heart disease cardiopulmonary bypass surgery gut microbiota biomarker |
| title | Predicting acute lung injury in infants with congenital heart disease after cardiopulmonary bypass by gut microbiota |
| title_full | Predicting acute lung injury in infants with congenital heart disease after cardiopulmonary bypass by gut microbiota |
| title_fullStr | Predicting acute lung injury in infants with congenital heart disease after cardiopulmonary bypass by gut microbiota |
| title_full_unstemmed | Predicting acute lung injury in infants with congenital heart disease after cardiopulmonary bypass by gut microbiota |
| title_short | Predicting acute lung injury in infants with congenital heart disease after cardiopulmonary bypass by gut microbiota |
| title_sort | predicting acute lung injury in infants with congenital heart disease after cardiopulmonary bypass by gut microbiota |
| topic | acute lung injury congenital heart disease cardiopulmonary bypass surgery gut microbiota biomarker |
| url | https://www.frontiersin.org/articles/10.3389/fimmu.2024.1362040/full |
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