Genetic Control of Human Brain Transcript Expression in Alzheimer Disease

Jennifer A. Webster, J. Raphael Gibbs, Jennifer Clarke, Monika Ray, Weixiong Zhang, Peter Holmans, Kristen Rohrer, Alice Zhao, Lauren Marlowe, Mona Kaleem, Donald S. McCorquodale, Cindy Cuello, Doris Leung, Leslie Bryden, Priti Nath, Victoria L. Zismann, Keta Joshipura, Matthew J. Huentelman, Diane Hu-Lince, Keith D. CoonDavid W. Craig, John V. Pearson, Christopher B. Heward, Eric M. Reiman, Dietrich Stephan, John Hardy, Amanda J. Myers

Research output: Contribution to journalArticlepeer-review

197 Scopus citations

Abstract

We recently surveyed the relationship between the human brain transcriptome and genome in a series of neuropathologically normal postmortem samples. We have now analyzed additional samples with a confirmed pathologic diagnosis of late-onset Alzheimer disease (LOAD; final n = 188 controls, 176 cases). Nine percent of the cortical transcripts that we analyzed had expression profiles correlated with their genotypes in the combined cohort, and approximately 5% of transcripts had SNP-transcript relationships that could distinguish LOAD samples. Two of these transcripts have been previously implicated in LOAD candidate-gene SNP-expression screens. This study shows how the relationship between common inherited genetic variants and brain transcript expression can be used in the study of human brain disorders. We suggest that studying the transcriptome as a quantitative endo-phenotype has greater power for discovering risk SNPs influencing expression than the use of discrete diagnostic categories such as presence or absence of disease.

Original languageEnglish (US)
Pages (from-to)445-458
Number of pages14
JournalAmerican journal of human genetics
Volume84
Issue number4
DOIs
StatePublished - Apr 10 2009

ASJC Scopus subject areas

  • Genetics
  • Genetics(clinical)

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