Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 572

The DOI matches its Crossref record; 44 of the 44 references it cites were found in a registry or an index.

Laboratory validation of a clinical metagenomic sequencing assay for pathogen detection in cerebrospinal fluid

Open access
Miller, Steve, Naccache, Samia N., Samayoa, Erik, Messacar, Kevin, Arevalo, Shaun, Federman, Scot, Stryke, Doug, Pham, Elizabeth, Fung, Becky, Bolosky, William J., Ingebrigtsen, Danielle, Lorizio, Walter, Paff, Sandra M., Leake, John A., Pesano, Rick, DeBiasi, Roberta, Dominguez, Samuel, Chiu, Charles Y.·2019·Genome Research

Published version of a preprint

Abstract

Metagenomic next-generation sequencing (mNGS) for pan-pathogen detection has been successfully tested in proof-of-concept case studies in patients with acute illness of unknown etiology but to date has been largely confined to research settings. Here, we developed and validated a clinical mNGS assay for diagnosis of infectious causes of meningitis and encephalitis from cerebrospinal fluid (CSF) in a licensed microbiology laboratory. A customized bioinformatics pipeline, SURPI+, was developed to rapidly analyze mNGS data, generate an automated summary of detected pathogens, and provide a graphical user interface for evaluating and interpreting results. We established quality metrics, threshold values, and limits of detection of 0.2–313 genomic copies or colony forming units per milliliter for each representative organism type. Gross hemolysis and excess host nucleic acid reduced assay sensitivity; however, spiked phages used as internal controls were reliable indicators of sensitivity loss. Diagnostic test accuracy was evaluated by blinded mNGS testing of 95 patient samples, revealing 73% sensitivity and 99% specificity compared to original clinical test results, and 81% positive percent agreement and 99% negative percent agreement after discrepancy analysis. Subsequent mNGS challenge testing of 20 positive CSF samples prospectively collected from a cohort of pediatric patients hospitalized with meningitis, encephalitis, and/or myelitis showed 92% sensitivity and 96% specificity relative to conventional microbiological testing of CSF in identifying the causative pathogen. These results demonstrate the analytic performance of a laboratory-validated mNGS assay for pan-pathogen detection, to be used clinically for diagnosis of neurological infections from CSF.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1101/gr.238170.118

Cites

44 of 44 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 44 references

Cited by

See all 572

Metadata

Authors
Miller, S., Naccache, S. N., Samayoa, E., Messacar, K., Arevalo, S., Federman, S., Stryke, D., Pham, E., Fung, B., Bolosky, W. J., Ingebrigtsen, D., Lorizio, W., Paff, S. M., Leake, J. A., Pesano, R., DeBiasi, R., Dominguez, S., & Chiu, C. Y.
Venue
Genome Research
Published
2019-04-16
Volume
29
Issue
5
Pages
831-842
ISSN
  • 1088-9051 (ISSN-L)
  • 1549-5469
OpenAlex
W2951983907
Cited by
572
References
44
Type
posted content
Language
en
Open access
bronze
Funders
  • National Institutes of Health (R01 HL105704, R21/R33 AI120977)
  • UC Center for Accelerated Innovation
  • NIH (U54 HL119893)
  • NCATS UCSF-CTSI (UL1 TR000004)
  • California Initiative to Advance Precision Medicine
  • Abbott Laboratories, Inc.
  • UCSF Medical Center

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Laboratory validation of a clinical metagenomic sequencing assay for pathogen detection in cerebrospinal fluid. https://app.cochat.ai/papers/10.1101/gr.238170.118
The paper
Miller, S., Naccache, S. N., Samayoa, E., Messacar, K., Arevalo, S., Federman, S., Stryke, D., Pham, E., Fung, B., Bolosky, W. J., Ingebrigtsen, D., Lorizio, W., Paff, S. M., Leake, J. A., Pesano, R., DeBiasi, R., Dominguez, S., & Chiu, C. Y. (2019). Laboratory validation of a clinical metagenomic sequencing assay for pathogen detection in cerebrospinal fluid. Genome Research. https://doi.org/10.1101/gr.238170.118

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.