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Purifying the Impure: Sequencing Metagenomes and Metatranscriptomes from Complex Animal-associated Samples
Published on: December 22, 2014
Microbial spectrum, co-detection patterns, and clinical correlations in 10,153 hospitalized children with acute
Chunyun Fu1, Junming Lu1, Xuehua Hu1
1Medical Science Laboratory, Children's Hospital, Maternal and Child Health Hospital of Guangxi Zhuang Autonomous Region, Nanning, 530003, People's Republic of China.
Insights
This study analyzed hospitalized children with acute respiratory infections (ARI), finding that specific microbes and their co-detection influence disease severity. Identifying predictors like respiratory complications aids in early risk stratification for better management.
Area of Science:
- Pediatric Infectious Diseases
- Microbiology
- Genomic Medicine
Background:
- Acute respiratory infections (ARI) are a major cause of hospitalization in children.
- Understanding the microbial causes and clinical spectrum of ARI is crucial for effective treatment.
- Targeted next-generation sequencing (tNGS) offers a comprehensive approach to identifying respiratory pathogens.
Purpose of the Study:
- To characterize the microbial spectrum and clinical manifestations in hospitalized children with ARI.
- To identify predictors of severe disease requiring intensive care unit (ICU) admission.
- To explore the impact of microbial co-detections on disease severity and outcomes.
Main Methods:
- Enrollment of 10,153 hospitalized children diagnosed with ARI.
- Utilizing tNGS on pediatric respiratory tract samples for microbial detection.
- Analyzing epidemiological, clinical, laboratory, and imaging data.
- Employing logistic regression to identify factors associated with ICU admission.
Main Results:
- High microbial detection rate (97.77%) with frequent co-detections (82.87%).
- Distinct clinical profiles linked to specific microbes: human respiratory syncytial virus (HRSV) and human bocavirus associated with severe disease in younger children; Mycoplasma pneumoniae (MP) with complications but lower overall severity in older children; adenovirus and Haemophilus influenzae with milder illness.
- A bidirectional severity pattern observed: higher virulence agents' single detection correlated with increased severity, while co-detection with lower-pathogenicity microbes like MP showed the opposite effect.
- Independent predictors for ICU admission included respiratory complications (OR=8.289), fever (OR=7.338), and other system complications (OR=5.564).
Conclusions:
- Complex co-detection patterns and microbe-dependent outcomes significantly impact ARI in hospitalized children.
- A novel bidirectional severity pattern and distinct ICU microbial profiles were identified.
- Robust predictive factors for ICU admission were established, enabling early risk stratification and tailored management strategies.
Objective:
This study characterized the microbial spectrum and clinical manifestations in hospitalized children with acute respiratory infections (ARI) using targeted next-generation sequencing (tNGS) and identified predictors for severe disease requiring ICU admission.
Methods:
10,153 hospitalized children with ARI were enrolled. Microbial detection was performed using tNGS on pediatric respiratory tract samples. Epidemiological trends, clinical features, laboratory and imaging findings, and outcomes were analyzed. Logistic regression identified factors associated with ICU admission.
Results:
The microbial detection rate was 97.77%, with a co-detection rate of 82.87%. Distinct clinical profiles emerged: human respiratory syncytial virus (HRSV) and human bocavirus were associated with younger age and more severe disease; Mycoplasma pneumoniae (MP) with frequent respiratory complications yet lower overall severity, particularly in older children; and adenovirus and Haemophilus influenzae with milder illness. A bidirectional severity pattern was identified: monodetections of higher-virulence agents (e.g., HRSV, Acinetobacter baumannii, human bocavirus) correlated with more severe disease than their co-detections, whereas the opposite was true for lower-pathogenicity microbes such as MP, adenovirus, and Haemophilus influenzae. ICU patients had significantly higher detection rates of HRSV (29.01% vs. 17.53%), cytomegalovirus (25.66% vs. 19.75%), and Acinetobacter baumannii (19.25% vs. 12.51%) (all P < 0.001). Independent predictors for ICU admission included respiratory complications (OR = 8.289), fever (OR = 7.338), and other system complications (OR = 5.564).
Conclusion:
This large-scale study uncovers complex co-detection patterns and microbe-dependent outcomes in ARI. A novel bidirectional severity pattern and distinct ICU microbial profiles with robust predictive factors have been identified, aiding early risk stratification and tailored management.
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