Impaired immune function in Gulf War Illness
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* Corresponding author: Toni Whistler taw6@cdc.gov
1 Chronic Viral Diseases Branch, Centers for Disease Control & Prevention, Atlanta, GA, USA
2 Medical Service, Miami Veterans Affairs Medical Center, Miami, FL, USA
3 Department of Medicine, University of Miami Miller School of Medicine, Miami, FL, USA
4 Current address : The Chronic Fatigue and Immune Dysfunction Syndromes (CFIDS) Association of America, Charlotte, NC, USA
BMC Medical Genomics 2009, 2:12 doi:10.1186/1755-8794-2-12
Published: 5 March 2009Additional files
Additional file 1:
Primers and probes sequences used for gene expression validation by real-time PCR. When available primer/probe sequences were used from the RTPrimerDB [19]http://medgen.ugent.be/rtprimerdb/ webcite. Italicized probes were designed using Primer Express software (v2.0). Where ever possible assays were used that crossed splice junctions. Probes were 5' labeled with 6-carboxyfluorescein (FAM) and 3' labeled with MGB non-fluorescent quencher.
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Additional file 2:
Statistical analysis of laboratory measures by ANOVA for 2 (illness class) × 3 (time) repeated measures. All values are given as mean ± standard error of the mean. P-values in bold are significant at p < 0.05, those in italics are just above this cutoff. A double asterisk indicates significant differences between illness class at indicated time points (**). Significant time effects were determined for all measures (p < 0.001) except those marked with a hash (#). na – measures not taken. * Net concentrations in supernatants of PHA stimulated minus unstimulated blood cultures are expressed as pg/105 lymphocytes in the culture. * Net concentrations in supernatants of PHA stimulated minus unstimulated blood cultures are expressed as pg/105 lymphocytes in the culture.
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Additional file 3:
List of genes that correlated with the NK and B cell subsets in the QTA. The data provided represent the two gene lists derived from the correlation analysis of the gene expression normalized signal against the natural killer and B-cell numbers respectively.
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Additional file 4:
Comparison of expression data between GWI cases and controls for the genes correlated with NK cell numbers. Averaged gene expression data and log ratios of the time series data for GWI cases and controls for the 141 probe sets correlated to NK subset cell numbers.
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Additional file 5:
Comparison of fold changes in time series data determined by qPCR or gene expression signals for GWI cases and controls. A graphic representation of these data appears in additional file 6. na – data not available because of technical difficulties.
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Additional file 6:
Graphical representation of qPCR validation data. Relative quantities of mRNA transcripts in GWI cases and controls as measured by qPCR or oligonucleotide microarray gene expression. a) Validation results for the differentiation of GWI cases from controls from hierarchical clustering of NK cell number correlation data. b) Validation of the correlation QTA data. Data represents scaled averages of normalized signals ± standard deviation for both real-time RT-PCR data (qPCR) and array expression signal (GE) on samples from GWI cases (hatched bars) and controls (plain bars) for the 3 time points of the exercise challenge: T0 in blue, T1 in red and T2 in yellow. The graph shows similar performance despite different dynamic ranges for the 2 methodologies. For the genes examined expression was lower in cases compared to controls.
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