Integrating central nervous system metagenomics and host response for diagnosis of tuberculosis meningitis and its mimics

P. S. Ramachandran; A. Ramesh; F. V. Creswell; A. Wapniarski; R. Narendra; C. M. Quinn; E. B. Tran; M. K. Rutakingirwa; A. S. Bangdiwala; E. Kagimu; K. T. Kandole; K. C. Zorn; L. Tugume; J. Kasibante; K. Ssebambulidde; M. Okirwoth; N. C. Bahr; A. Musubire; C. P. Skipper; C. Fouassier; A. Lyden; P. Serpa; G. Castaneda; S. Caldera; V. Ahyong; J. L. DeRisi; C. Langelier; E. D. Crawford; D. R. Boulware; D. B. Meya; M. R. Wilson

doi:10.1038/s41467-022-29353-x

Integrating central nervous system metagenomics and host response for diagnosis of tuberculosis meningitis and its mimics

P. S. Ramachandran, A. Ramesh, F. V. Creswell, A. Wapniarski, R. Narendra, C. M. Quinn, E. B. Tran, M. K. Rutakingirwa, A. S. Bangdiwala, E. Kagimu, K. T. Kandole, K. C. Zorn, L. Tugume, J. Kasibante, K. Ssebambulidde, M. Okirwoth, N. C. Bahr, A. Musubire, C. P. Skipper, C. FouassierA. Lyden, P. Serpa, G. Castaneda, S. Caldera, V. Ahyong, J. L. DeRisi, C. Langelier, E. D. Crawford, D. R. Boulware, D. B. Meya, M. R. Wilson

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18 Scopus citations

Abstract

The epidemiology of infectious causes of meningitis in sub-Saharan Africa is not well understood, and a common cause of meningitis in this region, Mycobacterium tuberculosis (TB), is notoriously hard to diagnose. Here we show that integrating cerebrospinal fluid (CSF) metagenomic next-generation sequencing (mNGS) with a host gene expression-based machine learning classifier (MLC) enhances diagnostic accuracy for TB meningitis (TBM) and its mimics. 368 HIV-infected Ugandan adults with subacute meningitis were prospectively enrolled. Total RNA and DNA CSF mNGS libraries were sequenced to identify meningitis pathogens. In parallel, a CSF host transcriptomic MLC to distinguish between TBM and other infections was trained and then evaluated in a blinded fashion on an independent dataset. mNGS identifies an array of infectious TBM mimics (and co-infections), including emerging, treatable, and vaccine-preventable pathogens including Wesselsbron virus, Toxoplasma gondii, Streptococcus pneumoniae, Nocardia brasiliensis, measles virus and cytomegalovirus. By leveraging the specificity of mNGS and the sensitivity of an MLC created from CSF host transcriptomes, the combined assay has high sensitivity (88.9%) and specificity (86.7%) for the detection of TBM and its many mimics. Furthermore, we achieve comparable combined assay performance at sequencing depths more amenable to performing diagnostic mNGS in low resource settings.

Original language	English (US)
Article number	1675
Journal	Nature communications
Volume	13
Issue number	1
DOIs	https://doi.org/10.1038/s41467-022-29353-x
State	Published - Dec 2022

Bibliographical note

Funding Information:
This research was made possible through support from the National Institute of Allergy and Infectious Diseases grant R01AI145437 (M.R.W., D.R.B., P.S.R., A.R., D.B.M., C.L., and A.W.), National Institute of Neurologic Disorders and Stroke grants K08NS096117 (M.R.W.) and K23NS110470 (N.C.B.), American Academy of Neurology Clinical Research Training Scholarship P0534134 (P.S.R.), Weill Institute for Neurosciences Pilot Award for Junior Investigators in the Neurosciences (P.S.R.), The Australian Government Research Training Program Scholarship (P.S.R.), the Fogarty International Center R01NS086312 and D43TW009345 (C.P.S.), Chan Zuckerberg Biohub (C.L., E.D.C., V.A., and J.L.D.), UCSF School of Medicine (C.M.Q. and E.B.T.), the Westridge Foundation (M.R.W.), and Wellcome (210772/Z/18/Z, F.V.C.). We thank the patients and their families for participation in this study.

Funding Information:
This research was made possible through support from the National Institute of Allergy and Infectious Diseases grant R01AI145437 (M.R.W., D.R.B., P.S.R., A.R., D.B.M., C.L., and A.W.), National Institute of Neurologic Disorders and Stroke grants K08NS096117 (M.R.W.) and K23NS110470 (N.C.B.), American Academy of Neurology Clinical Research Training Scholarship P0534134 (P.S.R.), Weill Institute for Neurosciences Pilot Award for Junior Investigators in the Neurosciences (P.S.R.), The Australian Government Research Training Program Scholarship (P.S.R.), the Fogarty International Center R01NS086312 and D43TW009345 (C.P.S.), Chan Zuckerberg Biohub (C.L., E.D.C., V.A., and J.L.D.), UCSF School of Medicine (C.M.Q. and E.B.T.), the Westridge Foundation (M.R.W.), and Wellcome (210772/Z/18/Z, F.V.C.). We thank the patients and their families for participation in this study.

Publisher Copyright:
© 2022, The Author(s).

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Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't

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Ramachandran, P. S., Ramesh, A., Creswell, F. V., Wapniarski, A., Narendra, R., Quinn, C. M., Tran, E. B., Rutakingirwa, M. K., Bangdiwala, A. S., Kagimu, E., Kandole, K. T., Zorn, K. C., Tugume, L., Kasibante, J., Ssebambulidde, K., Okirwoth, M., Bahr, N. C., Musubire, A., Skipper, C. P., ... Wilson, M. R. (2022). Integrating central nervous system metagenomics and host response for diagnosis of tuberculosis meningitis and its mimics. Nature communications, 13(1), Article 1675. https://doi.org/10.1038/s41467-022-29353-x

Ramachandran, PS, Ramesh, A, Creswell, FV, Wapniarski, A, Narendra, R, Quinn, CM, Tran, EB, Rutakingirwa, MK, Bangdiwala, AS, Kagimu, E, Kandole, KT, Zorn, KC, Tugume, L, Kasibante, J, Ssebambulidde, K, Okirwoth, M, Bahr, NC, Musubire, A, Skipper, CP, Fouassier, C, Lyden, A, Serpa, P, Castaneda, G, Caldera, S, Ahyong, V, DeRisi, JL, Langelier, C, Crawford, ED, Boulware, DR, Meya, DB & Wilson, MR 2022, 'Integrating central nervous system metagenomics and host response for diagnosis of tuberculosis meningitis and its mimics', Nature communications, vol. 13, no. 1, 1675. https://doi.org/10.1038/s41467-022-29353-x

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title = "Integrating central nervous system metagenomics and host response for diagnosis of tuberculosis meningitis and its mimics",

abstract = "The epidemiology of infectious causes of meningitis in sub-Saharan Africa is not well understood, and a common cause of meningitis in this region, Mycobacterium tuberculosis (TB), is notoriously hard to diagnose. Here we show that integrating cerebrospinal fluid (CSF) metagenomic next-generation sequencing (mNGS) with a host gene expression-based machine learning classifier (MLC) enhances diagnostic accuracy for TB meningitis (TBM) and its mimics. 368 HIV-infected Ugandan adults with subacute meningitis were prospectively enrolled. Total RNA and DNA CSF mNGS libraries were sequenced to identify meningitis pathogens. In parallel, a CSF host transcriptomic MLC to distinguish between TBM and other infections was trained and then evaluated in a blinded fashion on an independent dataset. mNGS identifies an array of infectious TBM mimics (and co-infections), including emerging, treatable, and vaccine-preventable pathogens including Wesselsbron virus, Toxoplasma gondii, Streptococcus pneumoniae, Nocardia brasiliensis, measles virus and cytomegalovirus. By leveraging the specificity of mNGS and the sensitivity of an MLC created from CSF host transcriptomes, the combined assay has high sensitivity (88.9%) and specificity (86.7%) for the detection of TBM and its many mimics. Furthermore, we achieve comparable combined assay performance at sequencing depths more amenable to performing diagnostic mNGS in low resource settings.",

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note = "Funding Information: This research was made possible through support from the National Institute of Allergy and Infectious Diseases grant R01AI145437 (M.R.W., D.R.B., P.S.R., A.R., D.B.M., C.L., and A.W.), National Institute of Neurologic Disorders and Stroke grants K08NS096117 (M.R.W.) and K23NS110470 (N.C.B.), American Academy of Neurology Clinical Research Training Scholarship P0534134 (P.S.R.), Weill Institute for Neurosciences Pilot Award for Junior Investigators in the Neurosciences (P.S.R.), The Australian Government Research Training Program Scholarship (P.S.R.), the Fogarty International Center R01NS086312 and D43TW009345 (C.P.S.), Chan Zuckerberg Biohub (C.L., E.D.C., V.A., and J.L.D.), UCSF School of Medicine (C.M.Q. and E.B.T.), the Westridge Foundation (M.R.W.), and Wellcome (210772/Z/18/Z, F.V.C.). We thank the patients and their families for participation in this study. Funding Information: This research was made possible through support from the National Institute of Allergy and Infectious Diseases grant R01AI145437 (M.R.W., D.R.B., P.S.R., A.R., D.B.M., C.L., and A.W.), National Institute of Neurologic Disorders and Stroke grants K08NS096117 (M.R.W.) and K23NS110470 (N.C.B.), American Academy of Neurology Clinical Research Training Scholarship P0534134 (P.S.R.), Weill Institute for Neurosciences Pilot Award for Junior Investigators in the Neurosciences (P.S.R.), The Australian Government Research Training Program Scholarship (P.S.R.), the Fogarty International Center R01NS086312 and D43TW009345 (C.P.S.), Chan Zuckerberg Biohub (C.L., E.D.C., V.A., and J.L.D.), UCSF School of Medicine (C.M.Q. and E.B.T.), the Westridge Foundation (M.R.W.), and Wellcome (210772/Z/18/Z, F.V.C.). We thank the patients and their families for participation in this study. Publisher Copyright: {\textcopyright} 2022, The Author(s).",

year = "2022",

month = dec,

doi = "10.1038/s41467-022-29353-x",

language = "English (US)",

volume = "13",

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T1 - Integrating central nervous system metagenomics and host response for diagnosis of tuberculosis meningitis and its mimics

AU - Ramachandran, P. S.

AU - Ramesh, A.

AU - Creswell, F. V.

AU - Wapniarski, A.

AU - Narendra, R.

AU - Quinn, C. M.

AU - Tran, E. B.

AU - Rutakingirwa, M. K.

AU - Bangdiwala, A. S.

AU - Kagimu, E.

AU - Kandole, K. T.

AU - Zorn, K. C.

AU - Tugume, L.

AU - Kasibante, J.

AU - Ssebambulidde, K.

AU - Okirwoth, M.

AU - Bahr, N. C.

AU - Musubire, A.

AU - Skipper, C. P.

AU - Fouassier, C.

AU - Lyden, A.

AU - Serpa, P.

AU - Castaneda, G.

AU - Caldera, S.

AU - Ahyong, V.

AU - DeRisi, J. L.

AU - Langelier, C.

AU - Crawford, E. D.

AU - Boulware, D. R.

AU - Meya, D. B.

AU - Wilson, M. R.

N1 - Funding Information: This research was made possible through support from the National Institute of Allergy and Infectious Diseases grant R01AI145437 (M.R.W., D.R.B., P.S.R., A.R., D.B.M., C.L., and A.W.), National Institute of Neurologic Disorders and Stroke grants K08NS096117 (M.R.W.) and K23NS110470 (N.C.B.), American Academy of Neurology Clinical Research Training Scholarship P0534134 (P.S.R.), Weill Institute for Neurosciences Pilot Award for Junior Investigators in the Neurosciences (P.S.R.), The Australian Government Research Training Program Scholarship (P.S.R.), the Fogarty International Center R01NS086312 and D43TW009345 (C.P.S.), Chan Zuckerberg Biohub (C.L., E.D.C., V.A., and J.L.D.), UCSF School of Medicine (C.M.Q. and E.B.T.), the Westridge Foundation (M.R.W.), and Wellcome (210772/Z/18/Z, F.V.C.). We thank the patients and their families for participation in this study. Funding Information: This research was made possible through support from the National Institute of Allergy and Infectious Diseases grant R01AI145437 (M.R.W., D.R.B., P.S.R., A.R., D.B.M., C.L., and A.W.), National Institute of Neurologic Disorders and Stroke grants K08NS096117 (M.R.W.) and K23NS110470 (N.C.B.), American Academy of Neurology Clinical Research Training Scholarship P0534134 (P.S.R.), Weill Institute for Neurosciences Pilot Award for Junior Investigators in the Neurosciences (P.S.R.), The Australian Government Research Training Program Scholarship (P.S.R.), the Fogarty International Center R01NS086312 and D43TW009345 (C.P.S.), Chan Zuckerberg Biohub (C.L., E.D.C., V.A., and J.L.D.), UCSF School of Medicine (C.M.Q. and E.B.T.), the Westridge Foundation (M.R.W.), and Wellcome (210772/Z/18/Z, F.V.C.). We thank the patients and their families for participation in this study. Publisher Copyright: © 2022, The Author(s).

PY - 2022/12

Y1 - 2022/12

N2 - The epidemiology of infectious causes of meningitis in sub-Saharan Africa is not well understood, and a common cause of meningitis in this region, Mycobacterium tuberculosis (TB), is notoriously hard to diagnose. Here we show that integrating cerebrospinal fluid (CSF) metagenomic next-generation sequencing (mNGS) with a host gene expression-based machine learning classifier (MLC) enhances diagnostic accuracy for TB meningitis (TBM) and its mimics. 368 HIV-infected Ugandan adults with subacute meningitis were prospectively enrolled. Total RNA and DNA CSF mNGS libraries were sequenced to identify meningitis pathogens. In parallel, a CSF host transcriptomic MLC to distinguish between TBM and other infections was trained and then evaluated in a blinded fashion on an independent dataset. mNGS identifies an array of infectious TBM mimics (and co-infections), including emerging, treatable, and vaccine-preventable pathogens including Wesselsbron virus, Toxoplasma gondii, Streptococcus pneumoniae, Nocardia brasiliensis, measles virus and cytomegalovirus. By leveraging the specificity of mNGS and the sensitivity of an MLC created from CSF host transcriptomes, the combined assay has high sensitivity (88.9%) and specificity (86.7%) for the detection of TBM and its many mimics. Furthermore, we achieve comparable combined assay performance at sequencing depths more amenable to performing diagnostic mNGS in low resource settings.

AB - The epidemiology of infectious causes of meningitis in sub-Saharan Africa is not well understood, and a common cause of meningitis in this region, Mycobacterium tuberculosis (TB), is notoriously hard to diagnose. Here we show that integrating cerebrospinal fluid (CSF) metagenomic next-generation sequencing (mNGS) with a host gene expression-based machine learning classifier (MLC) enhances diagnostic accuracy for TB meningitis (TBM) and its mimics. 368 HIV-infected Ugandan adults with subacute meningitis were prospectively enrolled. Total RNA and DNA CSF mNGS libraries were sequenced to identify meningitis pathogens. In parallel, a CSF host transcriptomic MLC to distinguish between TBM and other infections was trained and then evaluated in a blinded fashion on an independent dataset. mNGS identifies an array of infectious TBM mimics (and co-infections), including emerging, treatable, and vaccine-preventable pathogens including Wesselsbron virus, Toxoplasma gondii, Streptococcus pneumoniae, Nocardia brasiliensis, measles virus and cytomegalovirus. By leveraging the specificity of mNGS and the sensitivity of an MLC created from CSF host transcriptomes, the combined assay has high sensitivity (88.9%) and specificity (86.7%) for the detection of TBM and its many mimics. Furthermore, we achieve comparable combined assay performance at sequencing depths more amenable to performing diagnostic mNGS in low resource settings.

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Integrating central nervous system metagenomics and host response for diagnosis of tuberculosis meningitis and its mimics

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