Host gene expression signatures of H1N1, H3N2, HRV, RSV virus infection in adults

Consider the problem of designing a panel of complex biomarkers to predict a patient's health or disease state when one can pair his or her current test sample, called a target sample, with the patient's previously acquired healthy sample, called a reference sample. As contrasted to a population averaged reference, this reference sample is individualized. Automated predictor algorithms that compare and contrast the paired samples to each other could result in a new generation of test panels that compare to a person's healthy reference to enhance predictive accuracy. This study develops such an individualized predictor and illustrates the added value of including the healthy reference for design of predictive gene expression panels. The objective is to predict each subject's state of infection, e.g., neither exposed nor infected, exposed but not infected, pre-acute phase of infection, acute phase of infection, post-acute phase of infection. Using gene microarray data collected in a large-scale serially sampled respiratory virus challenge study, we quantify the diagnostic advantage of pairing a person's baseline reference with his or her target sample. The data was collected over 7 different challenge studies performed by Duke University under a contract awarded by the DARPA Predicting Health and Disease program. These 7 challenge studies are referred to as RSV DEE1, H3N2 DEE2, H1N1 DEE3, H1N1 DEE4, H3N2 DEE5, HRV UVA, and HRV DUKE. These studies consist of 2886 microarray chips assaying 12,023 genes of 148 human volunteer subjects under 4 different inoculation regimes (HRV, RSV, H1N1, H3N2). [1] RSV DEE1 consists of 420 microarray chips assaying 12,023 genes of 20 human volunteer subjects. [2] H3N2 DEE2 consists of 355 microarray chips assaying 12,023 genes of 17 human volunteer subjects. [3] H1N1 DEE3 consists of 477 microarray chips assaying 12,023 genes of 24 human volunteer subjects. [4] H1N1 DEE4 consists of 386 microarray chips assaying 12,023 genes of 19 human volunteer subjects. [5] H3N2 DEE5 consists of 482 microarray chips assaying 12,023 genes of 21 human volunteer subjects. [6] HRV UVA consists of 295 microarray chips assaying 12,023 genes of 20 human volunteer subjects. [7] HRV DUKE consists of 471 microarray chips assaying 12,023 genes of 27 human volunteer subjects. During each challenge study, subjects had peripheral blood taken prior to inoculation with virus (baseline), immediately prior to inoculation (pre-challenge) and at set intervals following challenge. RNA was extracted at Expression Analysis (Durham, NC) from whole blood using the PAXgene™ 96 Blood RNA Kit (PreAnalytiX, Valencia, CA) employing the manufacturer's recommended protocol. While whole blood RNA is initially extracted, a secondary procedure (B-globin reduction) was then employed to remove the contribution of red blood cell (RBC) RNA to the total RNA. A set of four peptide nucleic acid (PNA) oligomers whose sequences are complementary to the 3' portions of the alpha and beta hemoglobin RNA transcripts were added to reduce globin RNA transcription due to RBC. The inhibition of globin cDNA synthesis dramatically reduces the relative amount of anti-sense, biotin-labeled cRNA corresponding to the hemoglobin transcripts. Hybridization and microarray data collection were performed using the Human Genome U133A 2.0 Array (Affymetrix, Santa Clara, CA) and expression profiles were pre-processed using robust multi-array (RMA) method. The subject designations including symptom status, infection/shedding status, infection onset and offset time can be found at the web link.