TY - JOUR
T1 - Surveillance of transcriptomes in basic military trainees with normal, febrile respiratory illness, and convalescent phenotypes
AU - Thach, D. C.
AU - Agan, B. K.
AU - Olsen, C.
AU - Diao, J.
AU - Lin, B.
AU - Gomez, J.
AU - Jesse, M.
AU - Jenkins, M.
AU - Rowley, R.
AU - Hanson, E.
AU - Tibbetts, C.
AU - Stenger, D. A.
AU - Walter, E.
AU - Demitry, P.
AU - Difato, T.
AU - Holliday, R.
AU - Kruzelock, R.
AU - Daum, L.
AU - Metzgar, D.
AU - Niemeyer, D.
AU - Russell, K.
AU - Archer, M.
AU - Bravo, R.
AU - Freed, N.
AU - Fuller, J.
AU - Gratwick, K.
AU - Johnson, B.
AU - Lawrence, E.
AU - Meador, C.
AU - Melgarejo, H.
AU - Mueller, K.
AU - Pearson, D.
AU - Purkayastha, A.
AU - Santiago, J.
AU - Seto, D.
AU - Stotler, F.
AU - Thornton, J.
AU - Wang, Z.
AU - Watson, D.
AU - Worthy, S.
AU - Vora, G.
AU - Grant, K.
AU - James, C.
N1 - Funding Information:
We thank the study participants and F Ligler and J Golden for reviewing the manuscript. This work was supported in part by the Defense Threat Reduction Agency, HQ USAF Surgeon General’s Office, Office of Naval Research, and the Naval Research Laboratory. The opinions and assertions contained herein are the private ones of the authors and are not to be construed as official or reflecting the views of the Department of Defense. The EOS Consortium is an Air Force Medical Service initiative comprised of: Sponsorship: P Demitry1, T Difato1; Executive Board: E Hanson4, R Holliday2, R Rowley4, C Tibbetts4; Operational Board: D Stenger10, E Walter5, J Diao2; Technical Advisors & Collaborators: R Kruzelock6, B Agan10, L Daum11, D Metzgar12, D Niemeyer11, K Russell12; Research & Clinical Staff: M Archer9, R Bravo3, N Freed12, J Fuller12, J Gomez3, K Gratwick12, M Jenkins10, M Jesse3, B Johnson3, E Lawrence3, B Lin8, C Meador9, H Melgarejo3, K Mueller9, C Olsen2, D Pearson3, A Purkayastha2, J Santiago3, D Seto7, F Stotler3, D Thach8, J Thornton9, Z Wang8, D Watson3, S Worthy3, G Vora8; Operations Support Staff: K Grant2, C James2. Affiliations: Dept. of 1USAF/SGR, 2USAF/SGR (Ctr), 3Lackland AFB,4George Washington University, 5Texas A&M University Systems, 6Virginia Tech, 7George Mason University, 8Naval Research Laboratory, 9NOVA Research Incorporated, 10Wilford Hall Medical Ctr, 11Air Force Institute for Operational Health, 12Navy Health Research Ctr.
PY - 2005/10
Y1 - 2005/10
N2 - Gene expression profiles permit analysis of host immune response at the transcriptome level. We used the Pax gene Blood RNA (PAX) System and Affymetrix microarrays (HG-U133A&B) to survey profiles in basic military trainees and to classify them as healthy, febrile respiratory illness (FRI) without adenovirus, FRI with adenovirus, and convalescent from FRI with adenovirus. We assessed quality metrics of RNA processing for microarrays. Class prediction analysis discovered nested sets of transcripts that could categorize the phenotypes with optimized accuracy of 99% (nonfebrile vs febrile, P<0.0005), 87% (healthy vs convalescent, P=0.001), and 91% (febrile without vs with adenovirus, P<0.0005). The discovered set for classification of nonfebrile vs febrile patients consisted of 40 transcripts with functions related to interferon induced genes, complement cascades, and TNF and IL1 signaling. The set of seven transcripts for distinguishing healthy vs convalescent individuals included those associated with ribosomal structure, humoral immunity, and cell adhesion. The set of 10 transcripts for distinguishing FRI without vs with adenovirus had functions related to interferon induced genes, IL1 receptor accessory protein, and cell interactions. These results are the first in vivo demonstration of classification of infectious diseases via host signature transcripts and move us towards using the transcriptome in biosurveillance.
AB - Gene expression profiles permit analysis of host immune response at the transcriptome level. We used the Pax gene Blood RNA (PAX) System and Affymetrix microarrays (HG-U133A&B) to survey profiles in basic military trainees and to classify them as healthy, febrile respiratory illness (FRI) without adenovirus, FRI with adenovirus, and convalescent from FRI with adenovirus. We assessed quality metrics of RNA processing for microarrays. Class prediction analysis discovered nested sets of transcripts that could categorize the phenotypes with optimized accuracy of 99% (nonfebrile vs febrile, P<0.0005), 87% (healthy vs convalescent, P=0.001), and 91% (febrile without vs with adenovirus, P<0.0005). The discovered set for classification of nonfebrile vs febrile patients consisted of 40 transcripts with functions related to interferon induced genes, complement cascades, and TNF and IL1 signaling. The set of seven transcripts for distinguishing healthy vs convalescent individuals included those associated with ribosomal structure, humoral immunity, and cell adhesion. The set of 10 transcripts for distinguishing FRI without vs with adenovirus had functions related to interferon induced genes, IL1 receptor accessory protein, and cell interactions. These results are the first in vivo demonstration of classification of infectious diseases via host signature transcripts and move us towards using the transcriptome in biosurveillance.
KW - Infection phenotypes
KW - Surveillance
KW - Transcriptome
UR - http://www.scopus.com/inward/record.url?scp=27844515156&partnerID=8YFLogxK
U2 - 10.1038/sj.gene.6364244
DO - 10.1038/sj.gene.6364244
M3 - Article
C2 - 16034474
AN - SCOPUS:27844515156
SN - 1466-4879
VL - 6
SP - 588
EP - 595
JO - Genes and Immunity
JF - Genes and Immunity
IS - 7
ER -