1. Volume 22, Issue 2, Pages 411-426 (January 2018)
Genomic Circuitry Underlying Immunological Response to Pediatric Acute Respiratory Infection 
Sarah E. Henrickson, Sasikanth Manne, Douglas V. Dolfi, Kathleen D. Mansfield, Kaela Parkhouse, Rakesh D. Mistry, Elizabeth R. Alpern, Scott E. Hensley, Kathleen E. Sullivan, Susan E. Coffin, E. John Wherry 
Cell Reports 
Volume 22, Issue 2, Pages (January 2018)
DOI: /j.celrep
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2. Cell Reports 2018 22, 411-426DOI: (10.1016/j.celrep.2017.12.043)
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3. Figure 1
Effect of Acute Pediatric Upper Respiratory Viral Infection on CD8+ T Cell Gene Expression
(A) Heatmap of 100 genes most significantly different between CD8 T cells from HCs (HC) and patients with influenza-like illness (influenza virus [IFV], rhinovirus [HRV] or co-infection [IFV-HRV]). Row normalized z scores are presented.
(B) Heatmap of 20 class neighbors from the CD8 T cells from each of the four groups of patients (HC, IFV, IFV-HRV co-infection, and HRV). Row normalized z scores are presented.
(C) Three-dimensional partial least-squares discriminant analysis (PLS-DA) plot illustrating the differences in gene expression in CD8 T cells from IFV (red), IFV+HRV (blue), HC (light blue), and HRV (green).
(D and E) Circos plots and summary tables of GO biological process terms enrichment, demonstrating shared upregulation (D) and downregulation (E) of genes between CD8 T cells from groups of virally infected patients (e.g. IFV, IFV+HRV, and HRV) compared with HC (i.e. IFV versus HC compared with HRV versus HC). The p values are for the shared genes in the viral infections (denoted by the colored squares) versus HC. The summary table has the top 10 BP gene signatures by p value.
(F) Predicted upstream regulatory transcription factors for each group. Each group was compared with HC and the list of significant genes was calculated. IPA was used to determine the upstream genes most likely to be causative. The z scores are presented.
(G) Radar plots of the top three GSEA hallmark signatures for IFV, IFV-HRV, or HRV. The normalized enrichment scores from GSEA of hallmark gene sets are shown.
See also Figures S1–S3 and Tables S1 and S2.
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4. Figure 2
Effect of Pediatric Acute IFV Infection on CD8+ T Cell Gene Expression
(A) Heatmap of 100 genes most significantly different between CD8 T cells from HC and IFV patients.
(B) Three-dimensional PLS-DA plot displaying the differences between gene expression in CD8 T cells from HC (blue) and patients with IFV (red).
(C) Upstream regulator network for transcriptional changes in CD8 T cells from IFV patients. IPA was used to determine the upstream genes most likely to be causative.
(D) Top three GSEA hallmark signatures upregulated (top) and downregulated (lower) in CD8 T cells from patients with IFV versus HC.
(E) Selected GSEA MSigDB C7 signatures in CD8 T cells from patients with IFV versus HCs. GSE29615 (human PBMC control versus day 7 post-live-attenuated influenza vaccine, upregulated with vaccine); GSE29614 (human PBMC control versus day 7 post-trivalent-inactivated influenza vaccine, upregulated with vaccine); GSE13485 (human PBMC control versus yellow fever vaccine at day 7, upregulated with vaccine); GSE36476 (CD4 young versus elderly CD4 T memory cells, higher in young); GSE19825 (upregulated in mouse effector T cells at day 3.5 after LCMV infection versus naive cells); GSE24634 (upregulated in CD25+ T effector versus CD25− T effector cells after in vitro activation with interleukin-4 [IL-4]).
(F) Leading edge analysis of the manually selected C7 signatures in Figure 2E, with a heatmap including genes present in the LE of at least two gene signatures (black = included, gray = not included).
See also Table S3.
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5. Figure 3
WGCNA of Transcriptional Modules Correlated to Clinical Characteristics in Acute IFV
(A) Hierarchical clustering dendrogram of the 15 module eigengenes by WGCNA (top panel) and gene hierarchical clustering dendrogram (bottom panel).
(B) Gene expression module to clinical characteristic Pearson correlation coefficients (heatmap with color coding). Modules are shown on the bottom, and the upper table is a color scale for module-trait correlation. For each, GO BP signatures with an absolute correlation >0.5 and a correlation p value <0.05 were included.
(C–J) Four selected gene modules.
(C) D2, anti-correlated with current (2016) asthma status.
(D) E2, correlated with weight (kg) and age (years) and anti-correlated with concern for bacterial infection on the initial study visit.
(E) B3, correlated with male sex.
(F) A2, correlated with whether the patient returned to the PCP within one month.
(G) Network for module D2.
(H) Network for module E3.
(I) Network for module B3.
(J) Network for module A2.
For each, the list of GO BP signatures is listed to the left, and the network is presented to the right (G–J), respectively; smaller nodes have a p value >0.2 and larger nodes have a p value <0.2, color code as below networks). BP, biological process.
See also Table S4 and Figures S4 and S5.
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6. Figure 4 Developing and Validating an IPS for Gene Expression Data
(A) Strategy for designing IPS.
(B–C) IPS genes and their expression in IFV and HC. IPS score calculated as geometric mean of upregulated genes minus geometric mean of downregulated genes.
(B) Fold change of gene expression of each IPS member in all 4 training cohorts.
(C) Heatmap of IPS gene expression in HC and IFV-only patients from CHOP cohort.
(D) IPS score for HC (purple), HRV (green), IFV-HRV (blue), and IFV (red) within our CHOP dataset. IPS score calculated by sum of geometric mean of upregulated genes minus sum of geometric mean of downregulated genes.
(E) Assessment of IPS sensitivity. Left IPS score in a separate pediatric IFV cohort and right IPS score in a published adult IFV cohort (Parnell et al., 2011).
(F) Assessment of the sensitivity of the Influenza Meta-Signature (IMS) score (Andres-Terre et al., 2015). Left is the IMS score in our CHOP ILI cohort and right is the IMS score in a published adult IFV cohort (Parnell et al., 2011).
(G) Assessment of IPS score for HIV progressors versus non-progressors (Quigley et al., 2010) and chronic versus resolver HCV patients (Gupta et al., 2015) (left and right, respectively).
(H) Assessment of IMS score for (left) HIV progressors versus non-progressors and (right) chronic versus resolver HCV patients.
(I) Comparison of IPS with published IFV or bacterial/viral classification gene lists. The CHOP ILI dataset was used as a basis for calculating p values for two pan-age gene lists, three pediatric IFV gene lists, four pediatric ARTI gene lists, seven adult IFV gene lists, and two adult ARTI gene lists (including HC versus IFV, HC versus HRV, and HC versus IFV co-infected with HRV). The p values were calculated using Mann-Whitney; and top, CD8 T cells from IFV versus HC; middle, CD8 T cells from IFV+HRV versus HC. Lower, CD8 T cells from HRV versus HC. See also Figure S3 and Table S5 for dataset details and Table S6 for gene lists.
(J) IPS calculated for published dataset (Zhai et al., 2015) that tracks gene expression during acute ARTI (baseline, day 0, day 2, day 4, day 6, day 21, and the following spring) with IFV A, IFV B, IFV A+HRV, IFV B+HRV, and HRV alone.
See also Figure S6 and Table S5 and S6.
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7. Figure 5 Effect of Age on IPS
(A) IPS scores in our CHOP IFV dataset divided by age (<7 years versus >7 years) and comparing CD8 T cells from HC and IFV patients.
(B) Circos plots and tables of genes downregulated (upper) and upregulated (lower) between CD8 T cells from IFV patients <7 years and >7 years.
(C) Assessing the contribution of upregulated and downregulated genes to the IPS in each age group. Left, The difference in expression in upregulated genes comparing the four groups (young HC = <7 years, older HC = >7 years, young IFV = <7 years IFV, older IFV = >7 years IFV); middle, the difference in absolute expression of downregulated genes in CD8 T cells; right, the upregulated CD8+ T cell gene expression minus the downregulated CD8+ T cell gene expression (IPS score calculation).
(D) Networks of predicted upstream regulators in CD8 T cells from IFV patients <7 years of age (upper panel) and >7 years of age (lower panel) using IPA.
(E) Comprehensive ISG list based on the union of BP IFN-related lists was used to generate a heatmap of gene expression for CD8 T cells from HC and IFV patients by age.
See also Figure S7 and Table S7.
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8. Figure 6
Mechanisms Underlying Immune Response of Younger versus Older Childhood to Acute IFV Infection
(A) IPA was used to plot the IFN stimulated gene (ISG) pathway coded by gene upregulation (red nodes) and downregulation (green nodes) in IFV patients <7 years (upper panel) of age and >7 years of age (lower panel) when compared with healthy controls.
(B–E) NP ELISAs for H1 and H3 were performed.
(B) CHOP IFV patients, all ages, with correlation between IPS score and NP ELISA (includes both H1 and H3).
(C) CHOP IFV patients, all ages, with correlation between ISG score and NP ELISA (includes both H1 and H3).
(D) Left column, IPS correlated with NP (includes both H1 and H3); and right column, ISG correlated with NP (includes both H1 and H3). Top row, patients >7 years and with IFV. Middle row, patients <7 years and with IFV or IFV-HRV. Bottom row, patients <7 years with IFV only.
(E) Left column, STAT2 expression level and right column, STAT1 expression level. In all subplots, correlation of STATs with NP (includes both H1 and H3). Top row, patients >7 years and with IFV. Middle row, patients <7 years and with IFV or IFV-HRV. Bottom row, patients <7 years with IFV only.
See also Figure S7.
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