Journal
AMERICAN JOURNAL OF HUMAN GENETICS
Volume 84, Issue 4, Pages 445-458Publisher
CELL PRESS
DOI: 10.1016/j.ajhg.2009.03.011
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Funding
- Div Of Biological Infrastructure
- Direct For Biological Sciences [0743797] Funding Source: National Science Foundation
- Medical Research Council [G0801418, G0701075] Funding Source: researchfish
- MRC [G0801418, G0701075] Funding Source: UKRI
- Medical Research Council [G0701075, G0801418] Funding Source: Medline
- NIA NIH HHS [P30 AG019610, U01 AG016976] Funding Source: Medline
- NINDS NIH HHS [R01 NS059873] Funding Source: Medline
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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.
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