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      Genomics of ADME gene expression: mapping expression quantitative trait loci relevant for absorption, distribution, metabolism and excretion of drugs in human liver.

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          Abstract

          Expression quantitative trait loci (eQTL) analysis is a powerful approach toward identifying genetic loci associated with quantitative changes in gene expression. We applied genome-wide association analysis to a data set of >300 000 single-nucleotide polymorphisms and >48 000 mRNA expression phenotypes obtained by Illumina microarray profiling of 149 human surgical liver samples obtained from Caucasian donors with detailed medical documentation. Of 1226 significant associations, only 200 were validated when comparing with a previously published similar study. Potential explanations for low replication rate include differences in microarray platforms, statistical modeling, covariates considered and origin and collection procedures of tissues. Focused analysis revealed a subset of 95 associations related to absorption, distribution, metabolism and excretion of drugs. Of these, 21 were true replications and 74 were newly discovered associations in enzymes, transporters, transcriptional regulators and other genes. This study extends our knowledge about the genetics of inter-individual variability of gene expression with particular emphasis on pharmacogenomics.

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          Most cited references33

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          Genome-wide association studies for complex traits: consensus, uncertainty and challenges.

          The past year has witnessed substantial advances in understanding the genetic basis of many common phenotypes of biomedical importance. These advances have been the result of systematic, well-powered, genome-wide surveys exploring the relationships between common sequence variation and disease predisposition. This approach has revealed over 50 disease-susceptibility loci and has provided insights into the allelic architecture of multifactorial traits. At the same time, much has been learned about the successful prosecution of association studies on such a scale. This Review highlights the knowledge gained, defines areas of emerging consensus, and describes the challenges that remain as researchers seek to obtain more complete descriptions of the susceptibility architecture of biomedical traits of interest and to translate the information gathered into improvements in clinical management.
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            Six new loci associated with body mass index highlight a neuronal influence on body weight regulation.

            Common variants at only two loci, FTO and MC4R, have been reproducibly associated with body mass index (BMI) in humans. To identify additional loci, we conducted meta-analysis of 15 genome-wide association studies for BMI (n > 32,000) and followed up top signals in 14 additional cohorts (n > 59,000). We strongly confirm FTO and MC4R and identify six additional loci (P < 5 x 10(-8)): TMEM18, KCTD15, GNPDA2, SH2B1, MTCH2 and NEGR1 (where a 45-kb deletion polymorphism is a candidate causal variant). Several of the likely causal genes are highly expressed or known to act in the central nervous system (CNS), emphasizing, as in rare monogenic forms of obesity, the role of the CNS in predisposition to obesity.
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              Genetics of gene expression and its effect on disease.

              Common human diseases result from the interplay of many genes and environmental factors. Therefore, a more integrative biology approach is needed to unravel the complexity and causes of such diseases. To elucidate the complexity of common human diseases such as obesity, we have analysed the expression of 23,720 transcripts in large population-based blood and adipose tissue cohorts comprehensively assessed for various phenotypes, including traits related to clinical obesity. In contrast to the blood expression profiles, we observed a marked correlation between gene expression in adipose tissue and obesity-related traits. Genome-wide linkage and association mapping revealed a highly significant genetic component to gene expression traits, including a strong genetic effect of proximal (cis) signals, with 50% of the cis signals overlapping between the two tissues profiled. Here we demonstrate an extensive transcriptional network constructed from the human adipose data that exhibits significant overlap with similar network modules constructed from mouse adipose data. A core network module in humans and mice was identified that is enriched for genes involved in the inflammatory and immune response and has been found to be causally associated to obesity-related traits.
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                Author and article information

                Journal
                Pharmacogenomics J.
                The pharmacogenomics journal
                Springer Science and Business Media LLC
                1473-1150
                1470-269X
                Feb 2013
                : 13
                : 1
                Affiliations
                [1 ] Center for Bioinformatics Tuebingen (ZBIT), University of Tuebingen, Tuebingen, Germany.
                Article
                tpj201144
                10.1038/tpj.2011.44
                3564008
                22006096
                0b783ad1-c33c-4f19-a1f5-1baa1ca24e4b
                History

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