Abstract

Sample matching by inferred agonal stress in gene expression analyses of brain.

JZ Li; F Meng; L Tsavaler; SJ Evans; PV Choudary; H Tomita; MP Vawter; D Walsh; V Shokoohi; T Chung; WE Bunney; EG Jones; H Akil; SJ Watson; RM Myers
BMC Genomics. 2007; 8(336).

BACKGROUND: Gene expression patterns in the brain are strongly influenced by the severity and duration of physiological stress at the time of death. This agonal effect, if not well controlled, can lead to spurious findings and diminished statistical power in case-control comparisons. While some recent studies match samples by tissue pH and clinically recorded agonal conditions, we found that these indicators were sometimes at odds with observed stress-related gene expression patterns, and that matching by these criteria still sometimes results in identifying case-control differences that are primarily driven by residual agonal effects. This problem is analogous to the one encountered in genetic association studies, where self-reported race and ethnicity are often imprecise proxies for an individual's actual genetic ancestry. RESULTS: We developed an Agonal Stress Rating (ASR) system that evaluates each sample's degree of stress based on gene expression data, and used ASRs in post hoc sample matching or covariate analysis. While gene expression patterns are generally correlated across different brain regions, we found strong region-region differences in empirical ASRs in many subjects that likely reflect inter-individual variabilities in local structure or function, resulting in region-specific vulnerability to agonal stress. CONCLUSION: Variation of agonal stress across different brain regions differs between individuals, revealing a new level of complexity for gene expression studies of brain tissues. The Agonal Stress Ratings quantitatively assess each sample's extent of regulatory response to agonal stress, and allow a strong control of this important confounder.

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2213675/pdf/1471-2164-8-336.pdf