Limited Dynamic Range of Immune Response Gene Expression Observed in Healthy Blood Donors Using RT-PCR

Abstract

The use of quantitative gene expression analysis for the diagnosis, prognosis, and monitoring of disease requires the ability to distinguish pathophysiological changes from natural variations. To characterize these variations in apparently healthy subjects, quantitative real-time PCR was used to measure various immune response genes in whole blood collected from blood bank donors. In a single-time-point study of 131 donors, of 48 target genes, 43 were consistently expressed and 34 followed approximately log-normal distribution. Most transcripts showed a limited dynamic range of expression across subjects. Specifically, 36 genes had standard deviations (SDs) of 0.44 to 0.79 cycle threshold (C(T)) units, corresponding to less than a 3-fold variation in expression. Separately, a longitudinal study of 8 healthy individuals demonstrated a total dynamic range (> 2 standard error units) of 2- to 4-fold in most genes. In contrast, a study of whole blood gene expression in 6 volunteers injected with LPS showed 15 genes changing in expression 10- to 90-fold within 2 to 5 h and returning to within normal range within 21 hours. This work demonstrates that (1) the dynamic range of expression of many immune response genes is limited among healthy subjects; (2) expression levels for most genes analyzed are approximately log-normally distributed; and (3) individuals exposed to an infusion of bacterial endotoxin (lipopolysaccharide), show gene expression profiles that can be readily distinguished from those of a healthy population. These results suggest that normal reference ranges can be established for gene expression assays, providing critical standards for the diagnosis and management of disease.

Integrating Gene Transcription-Based Biomarkers to Understand Desert Tortoise and Ecosystem Health

“…In desert tortoises, determining a normal baseline for clinically healthy tortoises proved challenging. The transcript results taken as a whole weakly correlated with standard clinical assessments of health and may be more sensitive indicators of physiological perturbations (McLoughlin et al 2006). Standard clinical assessments of health, limited pathogen diagnostics, and generalized definitions and terminology associated with both may be inadequate to accurately reflect the health status of such wildlife species (Christopher et al 2003).…”

“…A key requirement for translation of gene transcript biomarker technology to clinical applications is the establishment of a normal or ''reference'' range of values, distinguishing between natural variation in gene transcript levels among healthy subjects and changes among those with compromised health (McLoughlin et al 2006). In desert tortoises, determining a normal baseline for clinically healthy tortoises proved challenging.…”

“…Commonly used parametric tests to distinguish differential gene transcription among populations were based partly on the assumption that the values being compared were sampled from normally distributed populations. We tested the assumption that transcript levels of our genes of interest were log-normally distributed, in order to use such tests for detection of disease or environmental stressors (McLoughlin et al 2006). Geometric means and 95% upper and lower confidence limits were computed, and Anderson-Darling and Shapiro-Wilk tests for normality were performed for all genes (NCSS, Statistical and Power Analysis Software, UT, USA).…”

“…Gene transcript analysis may improve the assessment of desert tortoises by detecting the earliest observable signs of physiological perturbation, as gene transcripts are typically evident prior to clinical manifestations to environmental stressors (McLoughlin et al 2006). Consequently, application of quantitative gene transcript analysis technology will likely provide an invaluable addition to current approaches for monitoring potential physiological impairment (McLoughlin et al 2006).…”

“…Consequently, application of quantitative gene transcript analysis technology will likely provide an invaluable addition to current approaches for monitoring potential physiological impairment (McLoughlin et al 2006). Herein, we describe the development of quantitative real-time polymerase chain reaction (qPCR) assays to measure differential transcript levels of multiple genes in the desert tortoise.…”