Cited by 980Bacterial Identification and Susceptibility TestingGenomics and Phylogenetic StudiesSepsis Diagnosis and Treatment

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Analytical and clinical validation of a microbial cell-free DNA sequencing test for infectious disease

Blauwkamp, Timothy A., Thair, Simone, Rosen, Michael J., Blair, Lily, Lindner, Martin S., Vilfan, Igor D., Kawli, Trupti, Christians, Fred C., Venkatasubrahmanyam, Shivkumar, Wall, Gregory D., Cheung, Anita, Rogers, Zoë N., Meshulam-Simon, Galit, Huijse, Liza, Balakrishnan, Sanjeev, Quinn, James V., Hollemon, Desiree, Hong, David K., Vaughn, Marla Lay, Kertesz, Mickey, Bercovici, Sivan, Wilber, Judith C., Yang, Samuel·2019·Nature Microbiology

DOI 10.1038/s41564-018-0349-6

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Abstract

Thousands of pathogens are known to infect humans, but only a fraction are readily identifiable using current diagnostic methods. Microbial cell-free DNA sequencing offers the potential to non-invasively identify a wide range of infections throughout the body, but the challenges of clinical-grade metagenomic testing must be addressed. Here we describe the analytical and clinical validation of a next-generation sequencing test that identifies and quantifies microbial cell-free DNA in plasma from 1,250 clinically relevant bacteria, DNA viruses, fungi and eukaryotic parasites. Test accuracy, precision, bias and robustness to a number of metagenomics-specific challenges were determined using a panel of 13 microorganisms that model key determinants of performance in 358 contrived plasma samples, as well as 2,625 infections simulated in silico and 580 clinical study samples. The test showed 93.7% agreement with blood culture in a cohort of 350 patients with a sepsis alert and identified an independently adjudicated cause of the sepsis alert more often than all of the microbiological testing combined (169 aetiological determinations versus 132). Among the 166 samples adjudicated to have no sepsis aetiology identified by any of the tested methods, sequencing identified microbial cell-free DNA in 62, likely derived from commensal organisms and incidental findings unrelated to the sepsis alert. Analysis of the first 2,000 patient samples tested in the CLIA laboratory showed that more than 85% of results were delivered the day after sample receipt, with 53.7% of reports identifying one or more microorganisms.

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Authors: Blauwkamp, T. A., Thair, S., Rosen, M. J., Blair, L., Lindner, M. S., Vilfan, I. D., Kawli, T., Christians, F. C., Venkatasubrahmanyam, S., Wall, G. D., Cheung, A., Rogers, Z. N., Meshulam-Simon, G., Huijse, L., Balakrishnan, S., Quinn, J. V., Hollemon, D., Hong, D. K., Vaughn, M. L., Kertesz, M., Bercovici, S., Wilber, J. C., & Yang, S.
Affiliations: Karius, Inc. (United States) (US)
Stanford University (US)
Corresponding author: Blauwkamp, Timothy A.
ORCID: Blauwkamp, Timothy A.
Thair, Simone
Rosen, Michael J.
Blair, Lily
Lindner, Martin S.
Vilfan, Igor D.
Christians, Fred C.
Meshulam-Simon, Galit
Huijse, Liza
Quinn, James V.
Hollemon, Desiree
Hong, David K.
Bercovici, Sivan
Yang, Samuel
Venue: Nature Microbiology
Publisher: Springer Science and Business Media LLC
Published: 2019-02-11
Volume: 4
Issue: 4
Pages: 663-674
ISSN: 2058-5276 (ISSN-L)
DOI: 10.1038/s41564-018-0349-6
OpenAlex: W2911798461
Cited by: 962
References: 53
Citations by year: 2026: 118 · 2025: 168 · 2024: 164 · 2023: 139 · 2022: 108 · 2021: 117 · 2020: 96 · 2019: 51
FWCI: 66.37
Type: journal article
Language: en
Open access: closed
Licence: www.springernature.com/gp/researchers/text-and-data-mining (tdm)
www.springernature.com/gp/researchers/text-and-data-mining (vor)
Locations: Nature Microbiology (publishedVersion)
PubMed (publishedVersion)
Funders: U.S. National Library of Medicine
Topics: Health Sciences › Medicine › Microbiology (medical) › Bacterial Identification and Susceptibility Testing
Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
Health Sciences › Medicine › Critical Care and Intensive Care Medicine › Sepsis Diagnosis and Treatment
Keywords: microbial cell-free DNA, metagenomic sequencing, infectious disease diagnosis, sepsis, non-invasive diagnosis, test validation, blood culture comparison, commensal organisms, incidental finding, DNA viruses, fungi, eukaryotic parasites
MeSH terms: Cell-Free Nucleic Acids, Communicable Diseases, DNA, Bacterial, DNA, Fungal, DNA, Viral, Humans, Cohort Studies, Sepsis, High-Throughput Nucleotide Sequencing

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Analytical and clinical validation of a microbial cell-free DNA sequencing test for infectious disease

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