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Open Access Research article

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

Jun Z Li12*, Fan Meng3, Larisa Tsavaler1, Simon J Evans3, Prabhakara V Choudary4, Hiroaki Tomita5, Marquis P Vawter5, David Walsh5, Vida Shokoohi1, Tisha Chung1, William E Bunney5, Edward G Jones4, Huda Akil3, Stanley J Watson3 and Richard M Myers12

Author Affiliations

1 Stanford Human Genome Center, Stanford University, Palo Alto, CA, USA

2 Department of Genetics, Stanford University, Palo Alto, CA, USA

3 Molecular & Behavioral Neuroscience Institute, University of Michigan, Ann Arbor, MI, USA

4 Center for Neuroscience, University of California, Davis, CA, USA

5 Department of Psychiatry & Human Behavior, University of California, Irvine, CA, USA

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BMC Genomics 2007, 8:336  doi:10.1186/1471-2164-8-336

Published: 24 September 2007

Abstract

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.