Rapid, Sample-to-Answer Host Gene Expression Test to Diagnose Viral Infection
Distinguishing bacterial, viral, or other etiologies of acute illness is diagnostically challenging with significant implications for appropriate antimicrobial use. Host gene expression offers a promising approach, although no clinically useful test has been developed yet to accomplish this. Here, Q...
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Published in | Open forum infectious diseases Vol. 6; no. 11; p. ofz466 |
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Main Authors | , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
United States
Oxford University Press
01.11.2019
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Subjects | |
Online Access | Get full text |
ISSN | 2328-8957 2328-8957 |
DOI | 10.1093/ofid/ofz466 |
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Abstract | Distinguishing bacterial, viral, or other etiologies of acute illness is diagnostically challenging with significant implications for appropriate antimicrobial use. Host gene expression offers a promising approach, although no clinically useful test has been developed yet to accomplish this. Here, Qvella's FAST HR (Richmond Hill, Ontario, Canada) process was developed to quantify previously identified host gene expression signatures in whole blood in <45 minutes.
Whole blood was collected from 128 human subjects (mean age 47, range 18-88) with clinically adjudicated, microbiologically confirmed viral infection, bacterial infection, noninfectious illness, or healthy controls. Stabilized mRNA was released from cleaned and stabilized RNA-surfactant complexes using e-lysis, an electrical process providing a quantitative real-time reverse transcription polymerase chain reaction-ready sample. Threshold cycle values (C
) for 10 host response targets were normalized to hypoxanthine phosphoribosyltransferase 1 expression, a control mRNA. The transcripts in the signature were specifically chosen to discriminate viral from nonviral infection (bacterial, noninfectious illness, or healthy). Classification accuracy was determined using cross-validated sparse logistic regression.
Reproducibility of mRNA quantification was within 1 cycle as compared to the difference seen between subjects with viral versus nonviral infection (up to 5.0 normalized C
difference). Classification of 128 subjects into viral or nonviral etiologies demonstrated 90.6% overall accuracy compared to 82.0% for procalcitonin (
= .06). FAST HR achieved rapid and accurate measurement of the host response to viral infection in less than 45 minutes.
These results demonstrate the ability to translate host gene expression signatures to clinical platforms for use in patients with suspected infection.
NCT00258869. |
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AbstractList | Distinguishing bacterial, viral, or other etiologies of acute illness is diagnostically challenging with significant implications for appropriate antimicrobial use. Host gene expression offers a promising approach, although no clinically useful test has been developed yet to accomplish this. Here, Qvella's FAST HR (Richmond Hill, Ontario, Canada) process was developed to quantify previously identified host gene expression signatures in whole blood in <45 minutes.
Whole blood was collected from 128 human subjects (mean age 47, range 18-88) with clinically adjudicated, microbiologically confirmed viral infection, bacterial infection, noninfectious illness, or healthy controls. Stabilized mRNA was released from cleaned and stabilized RNA-surfactant complexes using e-lysis, an electrical process providing a quantitative real-time reverse transcription polymerase chain reaction-ready sample. Threshold cycle values (C
) for 10 host response targets were normalized to hypoxanthine phosphoribosyltransferase 1 expression, a control mRNA. The transcripts in the signature were specifically chosen to discriminate viral from nonviral infection (bacterial, noninfectious illness, or healthy). Classification accuracy was determined using cross-validated sparse logistic regression.
Reproducibility of mRNA quantification was within 1 cycle as compared to the difference seen between subjects with viral versus nonviral infection (up to 5.0 normalized C
difference). Classification of 128 subjects into viral or nonviral etiologies demonstrated 90.6% overall accuracy compared to 82.0% for procalcitonin (
= .06). FAST HR achieved rapid and accurate measurement of the host response to viral infection in less than 45 minutes.
These results demonstrate the ability to translate host gene expression signatures to clinical platforms for use in patients with suspected infection.
NCT00258869. Distinguishing bacterial, viral, or other etiologies of acute illness is diagnostically challenging with significant implications for appropriate antimicrobial use. Host gene expression offers a promising approach, although no clinically useful test has been developed yet to accomplish this. Here, Qvella's FAST HR (Richmond Hill, Ontario, Canada) process was developed to quantify previously identified host gene expression signatures in whole blood in <45 minutes.OBJECTIVEDistinguishing bacterial, viral, or other etiologies of acute illness is diagnostically challenging with significant implications for appropriate antimicrobial use. Host gene expression offers a promising approach, although no clinically useful test has been developed yet to accomplish this. Here, Qvella's FAST HR (Richmond Hill, Ontario, Canada) process was developed to quantify previously identified host gene expression signatures in whole blood in <45 minutes.Whole blood was collected from 128 human subjects (mean age 47, range 18-88) with clinically adjudicated, microbiologically confirmed viral infection, bacterial infection, noninfectious illness, or healthy controls. Stabilized mRNA was released from cleaned and stabilized RNA-surfactant complexes using e-lysis, an electrical process providing a quantitative real-time reverse transcription polymerase chain reaction-ready sample. Threshold cycle values (CT) for 10 host response targets were normalized to hypoxanthine phosphoribosyltransferase 1 expression, a control mRNA. The transcripts in the signature were specifically chosen to discriminate viral from nonviral infection (bacterial, noninfectious illness, or healthy). Classification accuracy was determined using cross-validated sparse logistic regression.METHODWhole blood was collected from 128 human subjects (mean age 47, range 18-88) with clinically adjudicated, microbiologically confirmed viral infection, bacterial infection, noninfectious illness, or healthy controls. Stabilized mRNA was released from cleaned and stabilized RNA-surfactant complexes using e-lysis, an electrical process providing a quantitative real-time reverse transcription polymerase chain reaction-ready sample. Threshold cycle values (CT) for 10 host response targets were normalized to hypoxanthine phosphoribosyltransferase 1 expression, a control mRNA. The transcripts in the signature were specifically chosen to discriminate viral from nonviral infection (bacterial, noninfectious illness, or healthy). Classification accuracy was determined using cross-validated sparse logistic regression.Reproducibility of mRNA quantification was within 1 cycle as compared to the difference seen between subjects with viral versus nonviral infection (up to 5.0 normalized CT difference). Classification of 128 subjects into viral or nonviral etiologies demonstrated 90.6% overall accuracy compared to 82.0% for procalcitonin (P = .06). FAST HR achieved rapid and accurate measurement of the host response to viral infection in less than 45 minutes.RESULTSReproducibility of mRNA quantification was within 1 cycle as compared to the difference seen between subjects with viral versus nonviral infection (up to 5.0 normalized CT difference). Classification of 128 subjects into viral or nonviral etiologies demonstrated 90.6% overall accuracy compared to 82.0% for procalcitonin (P = .06). FAST HR achieved rapid and accurate measurement of the host response to viral infection in less than 45 minutes.These results demonstrate the ability to translate host gene expression signatures to clinical platforms for use in patients with suspected infection.CONCLUSIONSThese results demonstrate the ability to translate host gene expression signatures to clinical platforms for use in patients with suspected infection.NCT00258869.CLINICAL TRIALS REGISTRATIONNCT00258869. Host gene expression signatures are a new approach to diagnose the etiology of acute respiratory illness, though none are clinically available. The FAST-ID system is a rapid sample-to-answer system that provides such a solution. |
Author | Mcclain, Micah T Ginsburg, Geoffrey S Alavie, Tino Parmar, Vilcy Talebpour, Abdossamad Samiei, Alaleh Woods, Christopher W Burke, Thomas W Henao, Ricardo Tsalik, Ephraim L Khine, Ayeaye |
AuthorAffiliation | 3 Qvella Corporation , Richmond Hill, Ontario, Canada 5 Pratt School of Engineering, Duke University , Durham, North Carolina, USA 4 Medicine Service, Durham Veterans Affairs Health Care System , Durham, North Carolina, USA 1 Duke Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University School of Medicine , Durham, North Carolina, USA 2 Emergency Medicine Service, Durham Veterans Affairs Health Care System , Durham, North Carolina, USA |
AuthorAffiliation_xml | – name: 4 Medicine Service, Durham Veterans Affairs Health Care System , Durham, North Carolina, USA – name: 2 Emergency Medicine Service, Durham Veterans Affairs Health Care System , Durham, North Carolina, USA – name: 5 Pratt School of Engineering, Duke University , Durham, North Carolina, USA – name: 1 Duke Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University School of Medicine , Durham, North Carolina, USA – name: 3 Qvella Corporation , Richmond Hill, Ontario, Canada |
Author_xml | – sequence: 1 givenname: Ephraim L surname: Tsalik fullname: Tsalik, Ephraim L organization: Duke Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA, Emergency Medicine Service, Durham Veterans Affairs Health Care System, Durham, North Carolina, USA – sequence: 2 givenname: Ayeaye surname: Khine fullname: Khine, Ayeaye organization: Qvella Corporation, Richmond Hill, Ontario, Canada – sequence: 3 givenname: Abdossamad surname: Talebpour fullname: Talebpour, Abdossamad organization: Qvella Corporation, Richmond Hill, Ontario, Canada – sequence: 4 givenname: Alaleh surname: Samiei fullname: Samiei, Alaleh organization: Qvella Corporation, Richmond Hill, Ontario, Canada – sequence: 5 givenname: Vilcy surname: Parmar fullname: Parmar, Vilcy organization: Qvella Corporation, Richmond Hill, Ontario, Canada – sequence: 6 givenname: Thomas W surname: Burke fullname: Burke, Thomas W organization: Duke Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA – sequence: 7 givenname: Micah T surname: Mcclain fullname: Mcclain, Micah T organization: Duke Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA, Medicine Service, Durham Veterans Affairs Health Care System, Durham, North Carolina, USA – sequence: 8 givenname: Geoffrey S surname: Ginsburg fullname: Ginsburg, Geoffrey S organization: Duke Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA – sequence: 9 givenname: Christopher W surname: Woods fullname: Woods, Christopher W organization: Duke Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA, Medicine Service, Durham Veterans Affairs Health Care System, Durham, North Carolina, USA – sequence: 10 givenname: Ricardo surname: Henao fullname: Henao, Ricardo organization: Duke Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA, Pratt School of Engineering, Duke University, Durham, North Carolina, USA – sequence: 11 givenname: Tino surname: Alavie fullname: Alavie, Tino organization: Qvella Corporation, Richmond Hill, Ontario, Canada |
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CitedBy_id | crossref_primary_10_1093_cid_ciab043 crossref_primary_10_1093_cid_ciad541 crossref_primary_10_1093_ofid_ofae729 crossref_primary_10_1001_jamanetworkopen_2022_7299 crossref_primary_10_1016_j_trsl_2020_02_005 crossref_primary_10_1136_bmjresp_2023_002001 crossref_primary_10_1111_eci_13626 crossref_primary_10_1038_s41598_023_49734_6 crossref_primary_10_1186_s13073_021_00924_9 |
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Copyright | Published by Oxford University Press on behalf of Infectious Diseases Society of America 2019. Published by Oxford University Press on behalf of Infectious Diseases Society of America 2019. 2019 |
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Keywords | molecular diagnostic techniques virus diseases infection gene expression profiling real-time polymerase chain reaction |
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