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Updated: Sep 8, 2025

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease
Published on: April 4, 2018
Diagnostic Performance of Metagenomic Next-Generation Sequencing in Pediatric Patients: A Retrospective Study in a
Yue Tao1, Hui Yan1, Yujie Liu2
1Pediatric Translational Medicine Institute, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Background:
Metagenomic next-generation sequencing (mNGS) has the potential to become a complementary, if not essential, test in some clinical settings. However, the clinical application of mNGS in a large population of children with various types of infectious diseases (IDs) has not been previously evaluated.
Methods:
From April 2019 to April 2021, 640 samples were collected at a single pediatric hospital and classified as ID [479 (74.8%)], non-ID [NID; 156 (24.4%)], and unknown cases [5 (0.8%)], according to the final clinical diagnosis. We compared the diagnostic performance in pathogen detection between mNGS and standard reference tests.
Results:
According to final clinical diagnosis, the sensitivity and specificity of mNGS were 75.0% (95% CI: 70.8%-79.2%) and 59.0% (95% CI: 51.3%-66.7%), respectively. For distinguishing ID from NID, the sensitivity of mNGS was approximately 45.0% higher than that of standard tests (75.0% vs 30.0%; P < 0.001). For fungal detection, mNGS showed positive results in 93.0% of cases, compared to 43.7% for standard tests (P < 0.001). Diagnostic information was increased in respiratory system samples through the addition of meta-transcriptomic sequencing. Further analysis also showed that the read counts in sequencing data were highly correlated with clinical diagnosis, regardless of whether infection was by single or multiple pathogens (Kendall's tau b = 0.484, P < 0.001).
Conclusions:
For pediatric patients in critical condition with suspected infection, mNGS tests can provide valuable diagnostic information to resolve negative or inconclusive routine test results, differentiate ID from NID cases, and facilitate accurate and effective clinical therapeutic decision-making.
Insights
Metagenomic next-generation sequencing (mNGS) offers valuable diagnostic insights for pediatric infectious diseases (IDs), outperforming standard tests in pathogen detection. This advanced molecular test aids in differentiating infections and guiding treatment decisions in critically ill children.
Area of Science:
- Clinical microbiology
- Molecular diagnostics
- Pediatric infectious diseases
Background:
- Metagenomic next-generation sequencing (mNGS) shows promise as a clinical diagnostic tool.
- Previous evaluations of mNGS in large pediatric populations with diverse infectious diseases (IDs) are limited.
Purpose of the Study:
- To evaluate the clinical application and diagnostic performance of mNGS in a large cohort of pediatric patients with suspected infectious diseases.
- To compare mNGS with standard reference tests for pathogen detection.
Main Methods:
- A prospective study collected 640 samples from pediatric patients between April 2019 and April 2021.
- Samples were classified as infectious disease (ID), non-infectious disease (NID), or unknown based on final clinical diagnosis.
- Diagnostic performance of mNGS was compared against standard reference tests.
Main Results:
- mNGS demonstrated a sensitivity of 75.0% and specificity of 59.0% for diagnosing infectious diseases.
- mNGS significantly improved sensitivity for distinguishing ID from NID cases (75.0% vs. 30.0%) and fungal detection (93.0% vs. 43.7%) compared to standard tests.
- Read counts in sequencing data correlated with clinical diagnosis, supporting its utility in single and multiple pathogen infections.
Conclusions:
- mNGS provides crucial diagnostic information for critically ill pediatric patients, especially when routine tests are negative or inconclusive.
- The test aids in differentiating infectious from non-infectious conditions, facilitating precise clinical and therapeutic decisions.
- Integrating meta-transcriptomic sequencing enhanced diagnostic yield in respiratory samples.
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