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author:("Shim, heeding")
1.  A statin-dependent QTL for GATM expression is associated with statin-induced myopathy 
Nature  2013;502(7471):377-380.
Statins are widely prescribed for lowering plasma low-density lipoprotein (LDL) concentrations and cardiovascular disease risk1, but there is considerable interindividual variation in treatment response2,3 and increasing concern regarding the potential for adverse effects, including myopathy4 and type 2 diabetes5. Despite evidence for substantial genetic influence on LDL concentrations6, pharmacogenomic trials have failed to identify genetic variations with large effects on either statin efficacy7-9 or toxicity10, and have yielded little information regarding mechanisms that modulate statin response. Here we identify a downstream target of statin treatment by screening for the effects of in vitro statin exposure on genetic associations with gene expression levels in lymphoblastoid cell lines derived from 480 participants of a clinical trial of simvastatin treatment7. This analysis identified six expression quantitative trait loci (eQTLs) that interacted with simvastatin exposure including rs9806699, a cis-eQTL for the gene GATM that encodes glycine amidinotransferase, a rate-limiting enzyme in creatine synthesis. We found this locus to be associated with incidence of statin-induced myotoxicity in two separate populations (meta-analysis odds ratio = 0.60, 95% confidence interval = 0.45-0.81, P=6.0×10-4). Furthermore, we found that GATM knockdown in hepatocyte-derived cell lines attenuated transcriptional response to sterol depletion, demonstrating that GATM may act as a functional link between statin-mediated cholesterol lowering and susceptibility to statin-induced myopathy.
doi:10.1038/nature12508
PMCID: PMC3933266  PMID: 23995691
2.  Genome-wide association studies using single-nucleotide polymorphisms versus haplotypes: an empirical comparison with data from the North American Rheumatoid Arthritis Consortium 
BMC Proceedings  2009;3(Suppl 7):S35.
The high genomic density of the single-nucleotide polymorphism (SNP) sets that are typically surveyed in genome-wide association studies (GWAS) now allows the application of haplotype-based methods. Although the choice of haplotype-based vs. individual-SNP approaches is expected to affect the results of association studies, few empirical comparisons of method performance have been reported on the genome-wide scale in the same set of individuals. To measure the relative ability of the two strategies to detect associations, we used a large dataset from the North American Rheumatoid Arthritis Consortium to: 1) partition the genome into haplotype blocks, 2) associate haplotypes with disease, and 3) compare the results with individual-SNP association mapping. Although some associations were shared across methods, each approach uniquely identified several strong candidate regions. Our results suggest that the application of both haplotype-based and individual-SNP testing to GWAS should be adopted as a routine procedure.
PMCID: PMC2795933  PMID: 20018026

Results 1-2 (2)