Integrating host response and unbiased microbe detection for lower respiratory tract infection diagnosis in critically ill adults
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Abstract
Lower respiratory tract infections (LRTIs) lead to more deaths each year than any other infectious disease category. Despite this, etiologic LRTI pathogens are infrequently identified due to limitations of existing microbiologic tests. In critically ill patients, noninfectious inflammatory syndromes resembling LRTIs further complicate diagnosis. To address the need for improved LRTI diagnostics, we performed metagenomic next-generation sequencing (mNGS) on tracheal aspirates from 92 adults with acute respiratory failure and simultaneously assessed pathogens, the airway microbiome, and the host transcriptome. To differentiate pathogens from respiratory commensals, we developed a rules-based model (RBM) and logistic regression model (LRM) in a derivation cohort of 20 patients with LRTIs or noninfectious acute respiratory illnesses. When tested in an independent validation cohort of 24 patients, both models achieved accuracies of 95.5%. We next developed pathogen, microbiome diversity, and host gene expression metrics to identify LRTI-positive patients and differentiate them from critically ill controls with noninfectious acute respiratory illnesses. When tested in the validation cohort, the pathogen metric performed with an area under the receiver-operating curve (AUC) of 0.96 (95% CI, 0.86–1.00), the diversity metric with an AUC of 0.80 (95% CI, 0.63–0.98), and the host transcriptional classifier with an AUC of 0.88 (95% CI, 0.75–1.00). Combining these achieved a negative predictive value of 100%. This study suggests that a single streamlined protocol offering an integrated genomic portrait of pathogen, microbiome, and host transcriptome may hold promise as a tool for LRTI diagnosis.
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A study of mNGS for respiratory pathogens in pneumonia found that culture-proven infection was associated with significantly lower respiratory microbiome diversity.
“For example, a study of mNGS for the identification of respiratory pathogens in patients with pneumonia found that individuals with culture-proven infection had significantly less diversity in their respiratory microbiome25.”
From Clinical metagenomics (2019) · cites this paper as [25]
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- Authors
- Langelier, C., Kalantar, K. L., Moazed, F., Wilson, M. R., Crawford, E. D., Deiss, T., Belzer, A., Bolourchi, S., Caldera, S., Fung, M., Jauregui, A., Malcolm, K., Lyden, A., Khan, L., Vessel, K., Quan, J., Zinter, M., Chiu, C. Y., Chow, E. D., Wilson, J., Miller, S., Matthay, M. A., Pollard, K. S., Christenson, S., Calfee, C. S., & DeRisi, J. L.
- Affiliations
- University of California, San Francisco (US)
- Chan Zuckerberg Biohub San Francisco (US)
- Stanford Medicine (US)
- Gladstone Institutes (US)
- Corresponding author
- DeRisi, Joseph L.
- ORCID
- Langelier, Charles
- Kalantar, Katrina L.
- Wilson, Michael R.
- Crawford, Emily D.
- Deiss, Thomas
- Belzer, Annika
- Caldera, Saharai
- Fung, Monica
- Malcolm, Katherine
- Lyden, Amy
- Quan, Jenai
- Zinter, Matt
- Chiu, Charles Y.
- Chow, Eric D.
- Miller, Steve
- Matthay, Michael A.
- Pollard, Katherine S.
- Christenson, Stephanie
- Calfee, Carolyn S.
- DeRisi, Joseph L.
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2018-11-27
- Volume
- 115
- Issue
- 52
- Pages
- E12353-E12362
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC6310811
- OpenAlex
- W2805442283
- Cited by
- 411
- References
- 63
- Citations by year
- 2026: 48 · 2025: 56 · 2024: 60 · 2023: 56 · 2022: 59 · 2021: 55 · 2020: 45 · 2019: 29 · 2018: 3
- FWCI
- 26.96
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion, cc-by-nc-nd)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
- Europe PMC (PubMed Central) (publishedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- HHS | NIH | National Heart, Lung, and Blood Institute (NHLBI K23HL138461-01A1, NHLBI K23HL123778, NHLBI K23 HL136844, R01HL110969, K24HL133390, R35HL140026)
- Chan Zuckerberg Biohub (n/a)
- Gladstone Institutes (n/a)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Clinical Biochemistry › Bacterial Identification and Susceptibility Testing
- Health Sciences › Medicine › Epidemiology › Pneumonia and Respiratory Infections
- Life Sciences › Immunology and Microbiology › Microbiology › Microbial infections and disease research
- Keywords
- lower respiratory tract infection, metagenomic next-generation sequencing, tracheal aspirate, acute respiratory failure, critically ill adults, airway microbiome, host transcriptome, pathogen detection, microbiome diversity, diagnostic biomarkers
- MeSH terms
- Whole Genome Sequencing, Adult, Aged, Aged, 80 and over, Female, Humans, Male, Middle Aged, Predictive Value of Tests, Respiratory Tract Infections, Cohort Studies, Case-Control Studies, Critical Illness, Sequence Analysis, DNA, Area Under Curve, Transcriptome, Microbiota
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