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Updated: Jun 16, 2026

Obtaining High Quality RNA from Single Cell Populations in Human Postmortem Brain Tissue
18:17

Obtaining High Quality RNA from Single Cell Populations in Human Postmortem Brain Tissue

Published on: August 6, 2009

A cross-laboratory comparison of expression profiling data from normal human postmortem brain.

M Mistry1, P Pavlidis

  • 1Canadian Institute of Health Research/Michael Smith Foundation for Health Research (CIHR/MSFHR) Graduate Program in Bioinformatics, University of British Columbia, BC, Canada.

Neuroscience
|February 9, 2010
PubMed
Summary
This summary is machine-generated.

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This study analyzed gene expression in post-mortem brain tissue, revealing significant impacts of age, gender, and postmortem interval. These factors are crucial for interpreting results in neuropsychiatric disease research.

Area of Science:

  • Neuroscience
  • Genomics
  • Bioinformatics

Background:

  • Post-mortem human brain tissue expression profiling is vital for understanding neuropsychiatric diseases and aging.
  • Factors like age, gender, and postmortem interval (PMI) can influence gene expression more than disease states.
  • Controlling for these biological variables is essential for accurate interpretation of disease-related molecular changes.

Purpose of the Study:

  • To conduct a comprehensive meta-analysis of genome-wide expression studies in normal human cortex.
  • To catalogue the effects of age, gender, postmortem interval, and brain pH on gene expression.
  • To generate "meta-signatures" for each factor to aid in interpreting disease studies.

Main Methods:

  • Performed a large-scale meta-analysis of existing genome-wide expression datasets from normal human cortex.

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Last Updated: Jun 16, 2026

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  • Identified and catalogued gene expression changes associated with age, gender, postmortem interval, and brain pH.
  • Validated findings through overlap with independent gene lists and by identifying novel genes.

    • Main Results:

    • Generated "meta-signatures" that represent gene expression changes associated with age, gender, postmortem interval, and brain pH.
    • Demonstrated significant overlap between meta-analysis results and independently curated gene lists.
    • Identified genes not significant in individual studies, highlighting the power of meta-analysis.
    • Observed that many schizophrenia candidate genes are present in the meta-signatures, indicating potential confounding effects.

    Conclusions:

    • Meta-analysis provides a robust method for cataloguing biological effects on gene expression in the human brain.
    • Age, gender, and postmortem interval significantly influence gene expression and must be carefully controlled in disease studies.
    • The generated meta-signatures offer critical insights for future research on brain diseases and aging.