Utilizing Metagenomic Next-Generation Sequencing (mNGS) for Rapid Pathogen Identification and to Inform Clinical Decision-Making: Results from a Large Real-World Cohort
Abstract Introduction Clinical metagenomic next-generation sequencing (mNGS) has proven to be a powerful diagnostic tool in pathogen detection. However, its clinical utility has not been thoroughly evaluated. Methods In this single-center prospective study at the First Affiliated Hospital of Soochow...
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| Format: | Article |
| Language: | English |
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Adis, Springer Healthcare
2023-03-01
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| Series: | Infectious Diseases and Therapy |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s40121-023-00790-5 |
| _version_ | 1827956689272307712 |
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| author | Jie Xu Peng Zhou Jia Liu Lina Zhao Hailong Fu Qingzhen Han Lin Wang Weiwei Wu Qiuxiang Ou Yutong Ma Jun He |
| author_facet | Jie Xu Peng Zhou Jia Liu Lina Zhao Hailong Fu Qingzhen Han Lin Wang Weiwei Wu Qiuxiang Ou Yutong Ma Jun He |
| author_sort | Jie Xu |
| collection | DOAJ |
| description | Abstract Introduction Clinical metagenomic next-generation sequencing (mNGS) has proven to be a powerful diagnostic tool in pathogen detection. However, its clinical utility has not been thoroughly evaluated. Methods In this single-center prospective study at the First Affiliated Hospital of Soochow University, a total of 228 samples from 215 patients suspected of having acute or chronic infections between June 2018 and December 2018 were studied. Samples that met the mNGS quality control (QC) criteria (N = 201) were simultaneously analyzed using conventional tests (CTs), including multiple clinical microbiological tests and real-time PCR (if applicable). Results Pathogen detection results of mNGS in the 201 QC-passed samples were compared to CTs and exhibited a sensitivity of 98.8%, specificity of 38.5%, and accuracy of 87.1%. Specifically, 109 out of 160 (68.1%) CT+/mNGS+ samples exhibited concordant results at the species/genus level, 25 samples (15.6%) showed overlapping results, while the remaining 26 samples (16.3%) had discordant results between the CT and mNGS assays. In addition, mNGS could identify pathogens at the species level, whereas only the genera of some pathogens could be identified by CT. In this cohort, mNGS results were used to guide treatment plans in 24 out of 41 cases that had available follow-up information, and the symptoms were improved in over 70% (17/24) of them. Conclusion Our data demonstrated the analytic performance of our mNGS pipeline for pathogen detection using a large clinical cohort and strongly supports the notion that in clinical practice, mNGS represents a valuable supplementary tool to CTs to rapidly determine etiological factors of various types of infection and to guide treatment decision-making. |
| first_indexed | 2024-04-09T15:07:40Z |
| format | Article |
| id | doaj.art-a1f7eb2851ac4fffbccd451b68083ed1 |
| institution | Directory Open Access Journal |
| issn | 2193-8229 2193-6382 |
| language | English |
| last_indexed | 2024-04-09T15:07:40Z |
| publishDate | 2023-03-01 |
| publisher | Adis, Springer Healthcare |
| record_format | Article |
| series | Infectious Diseases and Therapy |
| spelling | doaj.art-a1f7eb2851ac4fffbccd451b68083ed12023-04-30T11:22:55ZengAdis, Springer HealthcareInfectious Diseases and Therapy2193-82292193-63822023-03-011241175118710.1007/s40121-023-00790-5Utilizing Metagenomic Next-Generation Sequencing (mNGS) for Rapid Pathogen Identification and to Inform Clinical Decision-Making: Results from a Large Real-World CohortJie Xu0Peng Zhou1Jia Liu2Lina Zhao3Hailong Fu4Qingzhen Han5Lin Wang6Weiwei Wu7Qiuxiang Ou8Yutong Ma9Jun He10Clinical Laboratory Center, The First Affiliated Hospital of Soochow UniversityCenter of Translational Medicine and Clinical Laboratory, Dushu Lake Hospital Affiliated to Soochow UniversityDinfectome Inc.Department of Laboratory Medicine, Ren Ji Hospital, Shanghai Jiao Tong University School of MedicineClinical Laboratory Center, The First Affiliated Hospital of Soochow UniversityCenter of Translational Medicine and Clinical Laboratory, Dushu Lake Hospital Affiliated to Soochow UniversityCenter of Translational Medicine and Clinical Laboratory, Dushu Lake Hospital Affiliated to Soochow UniversityDinfectome Inc.Dinfectome Inc.Dinfectome Inc.Clinical Laboratory Center, The First Affiliated Hospital of Soochow UniversityAbstract Introduction Clinical metagenomic next-generation sequencing (mNGS) has proven to be a powerful diagnostic tool in pathogen detection. However, its clinical utility has not been thoroughly evaluated. Methods In this single-center prospective study at the First Affiliated Hospital of Soochow University, a total of 228 samples from 215 patients suspected of having acute or chronic infections between June 2018 and December 2018 were studied. Samples that met the mNGS quality control (QC) criteria (N = 201) were simultaneously analyzed using conventional tests (CTs), including multiple clinical microbiological tests and real-time PCR (if applicable). Results Pathogen detection results of mNGS in the 201 QC-passed samples were compared to CTs and exhibited a sensitivity of 98.8%, specificity of 38.5%, and accuracy of 87.1%. Specifically, 109 out of 160 (68.1%) CT+/mNGS+ samples exhibited concordant results at the species/genus level, 25 samples (15.6%) showed overlapping results, while the remaining 26 samples (16.3%) had discordant results between the CT and mNGS assays. In addition, mNGS could identify pathogens at the species level, whereas only the genera of some pathogens could be identified by CT. In this cohort, mNGS results were used to guide treatment plans in 24 out of 41 cases that had available follow-up information, and the symptoms were improved in over 70% (17/24) of them. Conclusion Our data demonstrated the analytic performance of our mNGS pipeline for pathogen detection using a large clinical cohort and strongly supports the notion that in clinical practice, mNGS represents a valuable supplementary tool to CTs to rapidly determine etiological factors of various types of infection and to guide treatment decision-making.https://doi.org/10.1007/s40121-023-00790-5Metagenomic next-generation sequencingPathogen detectionInfectious diseaseTreatment decision-making |
| spellingShingle | Jie Xu Peng Zhou Jia Liu Lina Zhao Hailong Fu Qingzhen Han Lin Wang Weiwei Wu Qiuxiang Ou Yutong Ma Jun He Utilizing Metagenomic Next-Generation Sequencing (mNGS) for Rapid Pathogen Identification and to Inform Clinical Decision-Making: Results from a Large Real-World Cohort Infectious Diseases and Therapy Metagenomic next-generation sequencing Pathogen detection Infectious disease Treatment decision-making |
| title | Utilizing Metagenomic Next-Generation Sequencing (mNGS) for Rapid Pathogen Identification and to Inform Clinical Decision-Making: Results from a Large Real-World Cohort |
| title_full | Utilizing Metagenomic Next-Generation Sequencing (mNGS) for Rapid Pathogen Identification and to Inform Clinical Decision-Making: Results from a Large Real-World Cohort |
| title_fullStr | Utilizing Metagenomic Next-Generation Sequencing (mNGS) for Rapid Pathogen Identification and to Inform Clinical Decision-Making: Results from a Large Real-World Cohort |
| title_full_unstemmed | Utilizing Metagenomic Next-Generation Sequencing (mNGS) for Rapid Pathogen Identification and to Inform Clinical Decision-Making: Results from a Large Real-World Cohort |
| title_short | Utilizing Metagenomic Next-Generation Sequencing (mNGS) for Rapid Pathogen Identification and to Inform Clinical Decision-Making: Results from a Large Real-World Cohort |
| title_sort | utilizing metagenomic next generation sequencing mngs for rapid pathogen identification and to inform clinical decision making results from a large real world cohort |
| topic | Metagenomic next-generation sequencing Pathogen detection Infectious disease Treatment decision-making |
| url | https://doi.org/10.1007/s40121-023-00790-5 |
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