A Host Transcriptional Signature for Presymptomatic Detection of Infection in Humans Exposed to Influenza H1N1 or H3N2

Abstract

There is great potential for host-based gene expression analysis to impact the early diagnosis of infectious diseases. In particular, the influenza pandemic of 2009 highlighted the challenges and limitations of traditional pathogen-based testing for suspected upper respiratory viral infection. We inoculated human volunteers with either influenza A (A/Brisbane/59/2007 (H1N1) or A/Wisconsin/67/2005 (H3N2)), and assayed the peripheral blood transcriptome every 8 hours for 7 days. Of 41 inoculated volunteers, 18 (44%) developed symptomatic infection. Using unbiased sparse latent factor regression analysis, we generated a gene signature (or factor) for symptomatic influenza capable of detecting 94% of infected cases. This gene signature is detectable as early as 29 hours post-exposure and achieves maximal accuracy on average 43 hours (p = 0.003, H1N1) and 38 hours (p-value = 0.005, H3N2) before peak clinical symptoms. In order to test the relevance of these findings in naturally acquired disease, a composite influenza A signature built from these challenge studies was applied to Emergency Department patients where it discriminates between swine-origin influenza A/H1N1 (2009) infected and non-infected individuals with 92% accuracy. The host genomic response to Influenza infection is robust and may provide the means for detection before typical clinical symptoms are apparent.

Immunologic Characterization of a Rhesus Macaque H1N1 Challenge Model for Candidate Influenza Virus Vaccine Assessment

“…3B). This association between interferon activity and clinical signs is similar to what has been documented in the context of human influenza virus responses (23). Interferon transcriptional activity was not found to be correlated (R 2 ϭ 0.001) with peak body temperature, thus suggesting that day 5 interferon activity is more closely associated with fever duration rather than fever intensity.…”

Transcriptional Profiling of the Immune Response to Marburg Virus Infection

“…A detailed comparison of how different viral infections stimulate different immune responses can be done using data sets tracking the response of NHP PBMCs to Lassa virus infection (26) and influenza virus infection (40) and of human PBMCs to influenza virus infection (33,34,41). Already, preliminary direct analysis has shown that large parts of the initial response to each of these viruses are the same but that unique differences in initial gene expression during viral infections exist and can be predictive of specific infections (27).…”

Host-Based Peripheral Blood Gene Expression Analysis for Diagnosis of Infectious Diseases

“…Gene expression-based classifiers have also been shown to differentiate between specific viral etiologies, as demonstrated by a 70-gene RSV transcriptional profile that successfully separated infants with RSV lower respiratory tract infection from those with HRV or influenza virus infection with 94% sensitivity and 98% specificity (18). In addition to successfully distinguishing viral and bacterial infections, a gene expression-based classifier of viral infection has also demonstrated the ability to diagnose subjects very early, during the presymptomatic phase, and to allow eventual severity prediction (9).…”

“…Since gene expression is rapidly altered in many cell types in response to a variety of exposures (including infection), utilizing this information has several advantages. For example, host-based gene expression has been proven to be able to distinguish active infection from colonization (7), to distinguish among broad pathogen classes (such as distinguishing viral from bacterial pathogens), and to provide prognostic information and disease severity prediction (8,9). Furthermore, the widespread availability of quantitative reverse transcriptase PCR (qRT-PCR) platforms in clinical laboratories allows gene expression-based diagnostics to be more easily and directly translatable to patient care.…”