2012. FilmArray® Measurement of Host Response Signatures RapidLy Discriminates Viral, Bacterial, and Non-infectious Etiologies of Illness

Tsalik, Ephraim L.; Henao, Ricardo; Aydın, Mert; Bullard, Charles; Montgomery, Jesse; Nawrocki, Jeff; Deneris, Maxcén; Gritzen, Craig; Jones, Jay; Crisp, Robert J.; McClain, Micah T.; Burke, Thomas W.; Ginsburg, Geoffrey S.; Hemmert, Andrew; Woods, Christopher W.

doi:10.1093/ofid/ofy210.1668

Cited by 9 publications

(7 citation statements)

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“…Clinic-ready platforms capable of operationalising PCR-based signatures of the size tested herein already exist, some of which are approved with point-of-care functionality, offering a proximal pathway to clinical application of these findings. 46 Thus, analysis of the evolution of gene expression-based biomarkers over time shows promise for driving development of diagnostics for early detection of viral exposure and infection that could prove useful for guiding administration of early effective therapy, quarantine decisions, and other clinical and public health interventions in the setting of endemic and pandemic infectious disease.…”

Section: Discussionmentioning

confidence: 99%

A blood-based host gene expression assay for early detection of respiratory viral infection: an index-cluster prospective cohort study

McClain

Constantine

Nicholson

et al. 2021

The Lancet Infectious Diseases

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Background Early and accurate identification of individuals with viral infections is crucial for clinical management and public health interventions. We aimed to assess the ability of transcriptomic biomarkers to identify naturally acquired respiratory viral infection before typical symptoms are present. Methods In this index-cluster study, we prospectively recruited a cohort of undergraduate students (aged 18–25 years) at Duke University (Durham, NC, USA) over a period of 5 academic years. To identify index cases, we monitored students for the entire academic year, for the presence and severity of eight symptoms of respiratory tract infection using a daily web-based survey, with symptoms rated on a scale of 0–4. Index cases were defined as individuals who reported a 6-point increase in cumulative daily symptom score. Suspected index cases were visited by study staff to confirm the presence of reported symptoms of illness and to collect biospecimen samples. We then identified clusters of close contacts of index cases (ie, individuals who lived in close proximity to index cases, close friends, and partners) who were presumed to be at increased risk of developing symptomatic respiratory tract infection while under observation. We monitored each close contact for 5 days for symptoms and viral shedding and measured transcriptomic responses at each timepoint each day using a blood-based 36-gene RT-PCR assay. Findings Between Sept 1, 2009, and April 10, 2015, we enrolled 1465 participants. Of 264 index cases with respiratory tract infection symptoms, 150 (57%) had a viral cause confirmed by RT-PCR. Of their 555 close contacts, 106 (19%) developed symptomatic respiratory tract infection with a proven viral cause during the observation window, of whom 60 (57%) had the same virus as their associated index case. Nine viruses were detected in total. The transcriptomic assay accurately predicted viral infection at the time of maximum symptom severity (mean area under the receiver operating characteristic curve [AUROC] 0·94 [95% CI 0·92–0·96]), as well as at 1 day (0·87 [95% CI 0·84–0·90]), 2 days (0·85 [0·82–0·88]), and 3 days (0·74 [0·71–0·77]) before peak illness, when symptoms were minimal or absent and 22 (62%) of 35 individuals, 25 (69%) of 36 individuals, and 24 (82%) of 29 individuals, respectively, had no detectable viral shedding. Interpretation Transcriptional biomarkers accurately predict and diagnose infection across diverse viral causes and stages of disease and thus might prove useful for guiding the administration of early effective therapy, quarantine decisions, and other clinical and public health interventions in the setting of endemic and pandemic infectious diseases. Funding US Defense Advanced Research Projects Agency.

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Section: Discussionmentioning

confidence: 99%

A blood-based host gene expression assay for early detection of respiratory viral infection: an index-cluster prospective cohort study

McClain

Constantine

Nicholson

et al. 2021

The Lancet Infectious Diseases

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“…In summary, we have shown that a single transcript (IFI27) detects SARS-CoV-2 infection with high accuracy. If translated to a near-patient diagnostic test (34, 35) , this transcript could have significant clinical utility by facilitating early case detection.…”

Section: Discussionmentioning

confidence: 99%

Blood transcriptional biomarkers of acute viral infection for detection of pre-symptomatic SARS-CoV-2 infection

Rosenheim

Bell

et al. 2021

Preprint

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We hypothesised that host-response biomarkers of viral infections may contribute to early identification of SARS-CoV-2 infected individuals, critical to breaking chains of transmission. We identified 20 candidate blood transcriptomic signatures of viral infection by systematic review and evaluated their ability to detect SARS-CoV-2 infection, compared to the gold-standard of virus PCR tests, among a prospective cohort of 400 hospital staff subjected to weekly testing when fit to attend work. The transcriptional signatures had limited overlap, but were mostly co-correlated as components of type 1 interferon responses. We reconstructed each signature score in blood RNA sequencing data from 41 individuals over sequential weeks spanning a first positive SARS-CoV-2 PCR, and after 6-month convalescence. A single blood transcript for IFI27 provided the highest accuracy for discriminating individuals at the time of their first positive viral PCR result from uninfected controls, with area under the receiver operating characteristic curve (AUROC) of 0.95 (95% confidence interval 0.91–0.99), sensitivity 0.84 (0.7–0.93) and specificity 0.95 (0.85–0.98) at a predefined test threshold. The test performed equally well in individuals with and without symptoms, correlated with viral load, and identified incident infections one week before the first positive viral PCR with sensitivity 0.4 (0.17–0.69) and specificity 0.95 (0.85–0.98). Our findings strongly support further urgent evaluation and development of blood IFI27 transcripts as a biomarker for early phase SARS-CoV-2 infection, for screening individuals such as contacts of index cases, in order to facilitate early case isolation and early antiviral treatments as they emerge.

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“…In summary, our findings suggest that a single transcript ( IFI27 ) discriminates between individuals with mild early SARS-CoV-2 infection and uninfected healthy individuals with high accuracy. If translated to a near-patient diagnostic test, 46 , 47 this transcript could have substantial clinical utility by facilitating early case detection.…”

Section: Discussionmentioning

confidence: 99%

Blood transcriptional biomarkers of acute viral infection for detection of pre-symptomatic SARS-CoV-2 infection: a nested, case-control diagnostic accuracy study

Rk¹,

Rosenheim²,

Bell³

et al. 2021

The Lancet Microbe

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Background We hypothesised that host-response biomarkers of viral infections might contribute to early identification of individuals infected with SARS-CoV-2, which is critical to breaking the chains of transmission. We aimed to evaluate the diagnostic accuracy of existing candidate whole-blood transcriptomic signatures for viral infection to predict positivity of nasopharyngeal SARS-CoV-2 PCR testing. Methods We did a nested case-control diagnostic accuracy study among a prospective cohort of health-care workers (aged ≥18 years) at St Bartholomew's Hospital (London, UK) undergoing weekly blood and nasopharyngeal swab sampling for whole-blood RNA sequencing and SARS-CoV-2 PCR testing, when fit to attend work. We identified candidate blood transcriptomic signatures for viral infection through a systematic literature search. We searched MEDLINE for articles published between database inception and Oct 12, 2020, using comprehensive MeSH and keyword terms for “viral infection”, “transcriptome”, “biomarker”, and “blood”. We reconstructed signature scores in blood RNA sequencing data and evaluated their diagnostic accuracy for contemporaneous SARS-CoV-2 infection, compared with the gold standard of SARS-CoV-2 PCR testing, by quantifying the area under the receiver operating characteristic curve (AUROC), sensitivities, and specificities at a standardised Z score of at least 2 based on the distribution of signature scores in test-negative controls. We used pairwise DeLong tests compared with the most discriminating signature to identify the subset of best performing biomarkers. We evaluated associations between signature expression, viral load (using PCR cycle thresholds), and symptom status visually and using Spearman rank correlation. The primary outcome was the AUROC for discriminating between samples from participants who tested negative throughout the study (test-negative controls) and samples from participants with PCR-confirmed SARS-CoV-2 infection (test-positive participants) during their first week of PCR positivity. Findings We identified 20 candidate blood transcriptomic signatures of viral infection from 18 studies and evaluated their accuracy among 169 blood RNA samples from 96 participants over 24 weeks. Participants were recruited between March 23 and March 31, 2020. 114 samples were from 41 participants with SARS-CoV-2 infection, and 55 samples were from 55 test-negative controls. The median age of participants was 36 years (IQR 27–47) and 69 (72%) of 96 were women. Signatures had little overlap of component genes, but were mostly correlated as components of type I interferon responses. A single blood transcript for IFI27 provided the highest accuracy for discriminating between test-negative controls and test-positive individuals at the time of their first positive SARS-CoV-2 PCR result, with AUROC of 0·95 (95% CI 0·91–0·99), sensitivity 0·84 (0·70–0·93), and specificity 0·95 (0·85–0·98) at a predefined...

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2012. FilmArray® Measurement of Host Response Signatures RapidLy Discriminates Viral, Bacterial, and Non-infectious Etiologies of Illness

Cited by 9 publications

References 0 publications

A blood-based host gene expression assay for early detection of respiratory viral infection: an index-cluster prospective cohort study

A blood-based host gene expression assay for early detection of respiratory viral infection: an index-cluster prospective cohort study

Blood transcriptional biomarkers of acute viral infection for detection of pre-symptomatic SARS-CoV-2 infection

Blood transcriptional biomarkers of acute viral infection for detection of pre-symptomatic SARS-CoV-2 infection: a nested, case-control diagnostic accuracy study

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