Reporting and interpretation of respiratory metagenomic results in clinical practice: a systematic review and consensus guidelines from the UK NHS Respiratory Metagenomics Network
Abstract
Metagenomic sequencing can identify pathogens directly from respiratory samples without the need for culture, but laboratories differ widely in how they interpret and report results. In the first consensus guidance worldwide, we synthesise current practice and identify gaps in knowledge. Reviewing the literature identified 53 studies involving more than 6,000 participants, finding current evidence is limited by inconsistent methods, risk of bias, and subjective interpretation. After expert workshops and a three-round Delphi process across six sites in the NHS Respiratory Metagenomics Network, nineteen specialists agreed on 28 recommendations. The guidance sets out practical principles for defining detection thresholds, using control samples to identify contamination, deciding which findings to report, and assessing whether detected organisms are clinically important. It also includes a decision aid for reporting respiratory metagenomic results. These recommendations aim to support more transparent and consistent clinical reporting while identifying priorities for validation and future research.
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BibTeX
@article{snell2026reporting,
title = {{Reporting and interpretation of respiratory metagenomic results in clinical practice: a systematic review and consensus guidelines from the UK NHS Respiratory Metagenomics Network}},
author = {Luke B. Snell and Rahul Batra and Judith Breuer and Julianne R. Brown and Jonathan D. Edgeworth and Vanya Gant and Theodore Gouliouris and Paul Grant and Steve Green and Robbie Hammond and James Hatcher and Catherine Houlihan and Muktar Ibrahim and Ana Lima Soares and Sophie May and Rebecca McHugh and Chloe Myers and Gaia Nebbia and Nicholas J. Norton and Poorvi Patel and Simon Rock and Kordo Saeed and Manoj Valappil and Tom G. S. Williams and Adela Alcolea-Medina},
journal = {Communications Medicine},
year = {2026},
month = nov,
doi = {10.1038/s43856-026-01968-x},
url = {https://www.nature.com/articles/s43856-026-01968-x},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Reporting and interpretation of respiratory metagenomic results in clinical practice: a systematic review and consensus guidelines from the UK NHS Respiratory Metagenomics Network
AU - Luke B. Snell
AU - Rahul Batra
AU - Judith Breuer
AU - Julianne R. Brown
AU - Jonathan D. Edgeworth
AU - Vanya Gant
AU - Theodore Gouliouris
AU - Paul Grant
AU - Steve Green
AU - Robbie Hammond
AU - James Hatcher
AU - Catherine Houlihan
AU - Muktar Ibrahim
AU - Ana Lima Soares
AU - Sophie May
AU - Rebecca McHugh
AU - Chloe Myers
AU - Gaia Nebbia
AU - Nicholas J. Norton
AU - Poorvi Patel
AU - Simon Rock
AU - Kordo Saeed
AU - Manoj Valappil
AU - Tom G. S. Williams
AU - Adela Alcolea-Medina
PY - 2026
DA - 2026/11/03
JO - Communications Medicine
DO - 10.1038/s43856-026-01968-x
UR - https://www.nature.com/articles/s43856-026-01968-x
AB - Metagenomic sequencing can identify pathogens directly from respiratory samples without the need for culture, but laboratories differ widely in how they interpret and report results. In the first consensus guidance worldwide, we synthesise current practice and identify gaps in knowledge. Reviewing the literature identified 53 studies involving more than 6,000 participants, finding current evidence is limited by inconsistent methods, risk of bias, and subjective interpretation. After expert workshops and a three-round Delphi process across six sites in the NHS Respiratory Metagenomics Network, nineteen specialists agreed on 28 recommendations. The guidance sets out practical principles for defining detection thresholds, using control samples to identify contamination, deciding which findings to report, and assessing whether detected organisms are clinically important. It also includes a decision aid for reporting respiratory metagenomic results. These recommendations aim to support more transparent and consistent clinical reporting while identifying priorities for validation and future research.
SN - 2730-664X
ER -