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  • Review Article
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Metagenomics for neurological infections — expanding our imagination

Nature Reviews Neurology volume 16, pages 547–556 (2020) Cite this article

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Abstract

Over the past two decades, the diagnosis rate for patients with encephalitis has remained poor despite advances in pathogen-specific testing such as PCR and antigen assays. Metagenomic next-generation sequencing (mNGS) of RNA and DNA extracted from cerebrospinal fluid and brain tissue now offers another strategy for diagnosing neurological infections. Given that mNGS simultaneously assays for a wide range of infectious agents in an unbiased manner, it can identify pathogens that were not part of a neurologist’s initial differential diagnosis either because of the rarity of the infection, because the microorganism has not been previously associated with a clinical phenotype or because it is a newly discovered organism. This Review discusses the technical advantages and pitfalls of cerebrospinal fluid mNGS in the context of patients with neuroinflammatory syndromes, including encephalitis, meningitis and myelitis. We also speculate on how mNGS testing potentially fits into current diagnostic testing algorithms given data on mNGS test performance, cost and turnaround time. Finally, the Review highlights future directions for mNGS technology and other hypothesis-free testing methodologies that are in development.

Key points

  • Meningoencephalitis remains a challenging diagnosis owing to the multitude of possible infectious and autoimmune causes.

  • Meningoencephalitis is associated with a high rate of morbidity and mortality and requires prompt diagnosis and treatment.

  • Metagenomic next-generation sequencing (mNGS) is now a clinically validated test for neuroinfectious diseases that can aid clinicians with a timely diagnosis.

  • mNGS can improve the detection of pathogens that were missed by clinicians or on standard direct testing.

  • mNGS does not perform well when indirect tests are required to make the diagnosis (for example, serology), when infections are compartmentalized and for certain low abundance pathogens.

  • The clinical context of the case is required when interpreting the results of mNGS.

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Fig. 1: Virtuous learning cycle with hypothesis-free diagnostics.
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Acknowledgements

The authors thank the many committed neurologists and other physicians around the world whose dogged pursuit of diagnoses in patients with complex neuroinflammatory diseases, combined with their collaborative spirit, have led to many of the landmark studies cited in this Review. The authors also thank the patients and families for their participation in the many research studies that have advanced the field of diagnostics for neurological infections. Lastly, they thank the many government and philanthropic foundations that have supported work in this area.

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  1. Weill Institute for Neurosciences, University of California, San Francisco, CA, USA

    Prashanth S. Ramachandran & Michael R. Wilson

  2. Department of Neurology, University of California, San Francisco, CA, USA

    Prashanth S. Ramachandran & Michael R. Wilson

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  1. Prashanth S. Ramachandran
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Both authors contributed equally to all aspects of the manuscript.

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Correspondence to Michael R. Wilson.

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Ramachandran, P.S., Wilson, M.R. Metagenomics for neurological infections — expanding our imagination. Nat Rev Neurol 16, 547–556 (2020). https://doi.org/10.1038/s41582-020-0374-y

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