Genetic Control of Human Brain Transcript Expression in Alzheimer Disease

Neurogenomics Division, Translational Genomics Research Institute, Phoenix, AZ 85004, USA.
The American Journal of Human Genetics (Impact Factor: 10.93). 05/2009; 84(4):445-58. DOI: 10.1016/j.ajhg.2009.03.011
Source: PubMed


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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    • "Transcriptome profiles from this series were obtained on an Illumina HT-12 microarray. All transcript profiles were corrected as in Webster et al. (2009) with the exception that the lumi R package was used for set 2 (Du et al., 2008). SNP genotypes from both sets were imputed using the same procedure as before, and Tagger was used as before to define minimal sets of variants to test. "
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    • "We tested replication of the DC pairs identified using the HBTRC samples in an independent human cohort of late-onset AD and control individuals (Webster et al, 2009). We obtained the expression data of that study from GEO (GSE15222), extracted the data of postmortem frontal cortex samples alone of 31 AD and 40 control individuals (over 24,354 transcripts, which became 23,613 unique transcripts after replacing transcripts represented by multiple probes with a randomly pre-selected probe), and adjusted through a linear regression model the AD and control group data separately for the same set of covariates used in the study. "
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    ABSTRACT: Using expression profiles from postmortem prefrontal cortex samples of 624 dementia patients and non-demented controls, we investigated global disruptions in the co-regulation of genes in two neurodegenerative diseases, late-onset Alzheimer's disease (AD) and Huntington's disease (HD). We identified networks of differentially co-expressed (DC) gene pairs that either gained or lost correlation in disease cases relative to the control group, with the former dominant for both AD and HD and both patterns replicating in independent human cohorts of AD and aging. When aligning networks of DC patterns and physical interactions, we identified a 242-gene subnetwork enriched for independent AD/HD signatures. This subnetwork revealed a surprising dichotomy of gained/lost correlations among two inter-connected processes, chromatin organization and neural differentiation, and included DNA methyltransferases, DNMT1 and DNMT3A, of which we predicted the former but not latter as a key regulator. To validate the inter-connection of these two processes and our key regulator prediction, we generated two brain-specific knockout (KO) mice and show that Dnmt1 KO signature significantly overlaps with the subnetwork (P = 3.1 × 10−12), while Dnmt3a KO signature does not (P = 0.017).
    Molecular Systems Biology 07/2014; 10(7). DOI:10.15252/msb.20145304 · 10.87 Impact Factor
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    • "Summary of Westra et al.[32]blood eQTL overlap with eQTL from Webster et al .[29]which were found to have an interaction with late-onset Alzheimer’s disease (AD) status as well as those independent of disease status "
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