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Numerous pharmacogenetic clinical guidelines and recommendations have been published, but barriers have hindered the clinical implementation of pharmacogenetics. The Translational Pharmacogenetics Program (TPP) of the National Institutes of Health (NIH) Pharmacogenomics Research Network was established in 2011 to catalog and contribute to the development of pharmacogenetic implementations at eight US healthcare systems, with the goal to disseminate real-world solutions for the barriers to clinical pharmacogenetic implementation. The TPP collected and normalized pharmacogenetic implementation metrics through June 2015, including gene-drug pairs implemented, interpretations of alleles and diplotypes, numbers of tests performed and actionable results, and workflow diagrams. TPP participant institutions developed diverse solutions to overcome many barriers, but the use of Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines provided some consistency among the institutions. The TPP also collected some pharmacogenetic implementation outcomes (scientific, educational, financial, and informatics), which may inform healthcare systems seeking to implement their own pharmacogenetic testing programs.

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Variation in the expression level and activity of genes involved in drug disposition and action ('pharmacogenes') can affect drug response and toxicity, especially when in tissues of pharmacological importance. Previous studies have relied primarily on microarrays to understand gene expression differences, or have focused on a single tissue or small number of samples. The goal of this study was to use RNA-sequencing (RNA-seq) to determine the expression levels and alternative splicing of 389 Pharmacogenomics Research Network pharmacogenes across four tissues (liver, kidney, heart and adipose) and lymphoblastoid cell lines, which are used widely in pharmacogenomics studies. Analysis of RNA-seq data from 139 different individuals across the 5 tissues (20-45 individuals per tissue type) revealed substantial variation in both expression levels and splicing across samples and tissue types. Comparison with GTEx data yielded a consistent picture. This in-depth exploration also revealed 183 splicing events in pharmacogenes that were previously not annotated. Overall, this study serves as a rich resource for the research community to inform biomarker and drug discovery and use.

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Tacrolimus is the mainstay immunosuppressant drug used after solid organ and hematopoietic stem cell transplantation. Individuals who express CYP3A5 (extensive and intermediate metabolizers) generally have decreased dose-adjusted trough concentrations of tacrolimus as compared with those who are CYP3A5 nonexpressers (poor metabolizers), possibly delaying achievement of target blood concentrations. We summarize evidence from the published literature supporting this association and provide dosing recommendations for tacrolimus based on CYP3A5 genotype when known (updates at www.pharmgkb.org).

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The association of nonfunctional variants of the cholesteryl ester transfer protein (CETP) with efficacy of statins has been a subject of debate. We evaluated whether three functional CETP variants influence statin efficacy. The effect of CETP genotype on achieved levels of high-density lipoprotein cholesterol (HDLc), low-density lipoprotein cholesterol (LDLc), and total cholesterol during statin treatment was estimated by meta-analysis of the linear regression outcomes of three studies (11,021 individuals). The effect of these single-nucleotide polymorphisms (SNPs) on statin response in protecting against myocardial infarction (MI) was estimated by meta-analysis of statin × SNP interaction terms from logistic regression in five studies (16,570 individuals). The enhancer SNP rs3764261 significantly increased HDLc by 0.02 mmol/l per T allele (P = 6 × 10(-5)) and reduced protection against MI by statins (interaction odds ratio (OR) = 1.19 per T allele; P = 0.04). Focusing on functional CETP variants, we showed that in carriers of the rs3764261 T variant, HDLc increased more during statin treatment, and protection against MI by statins appeared to be reduced as compared with those in noncarriers.

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The neuroprotective function of the blood-brain barrier (BBB) presents a major challenge for drug delivery to the central nervous system (CNS). Critical to this function, BBB membrane transporters include the ATP-binding cassette (ABC) transporters, which limit drug penetration across the BBB, and the less-well-studied solute carrier (SLC) transporters. In this work, expression profiling of 359 SLC transporters, comparative expression analysis with kidney and liver, and immunoassays in brain microvessels (BMVs) identified previously unknown transporters at the human BBB.

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Genetic variation in C-type lectins influences infectious disease susceptibility but remains poorly understood. We used allelic mRNA expression imbalance (AEI) technology for surfactant protein (SP)-A1, SP-A2, SP-D, dendritic cell-specific ICAM-3-grabbing non-integrin (DC-SIGN), macrophage mannose receptor (MRC1) and Dectin-1, expressed in human macrophages and/or lung tissues. Frequent AEI, an indicator of regulatory polymorphisms, was observed in SP-A2, SP-D and DC-SIGN. AEI was measured for SP-A2 in 38 lung tissues using four marker single-nucleotide polymorphisms (SNPs) and was confirmed by next-generation sequencing of one lung RNA sample. Genomic DNA at the SP-A2 DNA locus was sequenced by Ion Torrent technology in 16 samples. Correlation analysis of genotypes with AEI identified a haplotype block, and, specifically, the intronic SNP rs1650232 (30% minor allele frequency); the only variant consistently associated with an approximately twofold change in mRNA allelic expression. Previously shown to alter a NAGNAG splice acceptor site with likely effects on SP-A2 expression, rs1650232 generates an alternative splice variant with three additional bases at the start of exon 3. Validated as a regulatory variant, rs1650232 is in partial linkage disequilibrium with known SP-A2 marker SNPs previously associated with risk for respiratory diseases including tuberculosis. Applying functional DNA variants in clinical association studies, rather than marker SNPs, will advance our understanding of genetic susceptibility to infectious diseases.

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Epistatic gene-gene interactions could contribute to the heritability of complex multigenic disorders, but few examples have been reported. Here, we focus on the role of aberrant dopaminergic signaling, involving the dopamine transporter DAT, a cocaine target, and the dopamine D2 receptor, which physically interacts with DAT. Splicing polymorphism rs2283265 of DRD2, encoding D2 receptors, were shown to confer risk of cocaine overdose/death (odds ratio ∼3) in subjects and controls from the Miami Dade County Brain Bank.(1) Risk of cocaine-related death attributable to the minor allele of rs2283265 was significantly enhanced to OR=7.5 (P=0.0008) in homozygous carriers of the main 6-repeat allele of DAT rs3836790, a regulatory VNTR in intron8 lacking significant effect itself. In contrast, carriers of the minor 5-repeat DAT allele showed no significant risk (OR=1.1, P=0.84). DAT rs3836790 and DRD2 rs2283265 also interacted by modulating DAT protein activity in the ventral putamen of cocaine abusers. In high-linkage disequilibrium with the VNTR, DAT rs6347 in exon9 yielded similar results. Assessing the impact of DAT alone, a rare DAT haplotype formed by the minor alleles of rs3836790 and rs27072, a regulatory DAT variant in the 3'-UTR, occurred in nearly one-third of the cocaine abusers but was absent in African American controls, apparently conferring strong risk. These results demonstrate gene-gene-drug interaction affecting risk of fatal cocaine intoxication.

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The use of pharmacogenomic biomarkers can enhance treatment outcomes. Regulatory polymorphisms are promising biomarkers that have proven difficult to uncover. They come in two flavors: those that affect transcription (regulatory single-nucleotide polymorphisms (rSNPs)) and those that affect RNA functions such as splicing, turnover, and translation (termed structural RNA SNPs (srSNPs)). This review focuses on the role of srSNPs in drug metabolism, transport, and response. An understanding of the nature and diversity of srSNPs and rSNPs enables clinical scientists to evaluate genetic biomarkers.

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Cytochrome P450 3A4 (CYP3A4) metabolizes ∼50% of all clinically used drugs. Although CYP3A4 expression varies widely between individuals, the contribution of genetic factors remains uncertain. In this study, we measured allelic CYP3A4 heteronuclear RNA (hnRNA) and mRNA expression in 76 human liver samples heterozygous for at least one of eight marker SNPs and found marked allelic expression imbalance (1.6-6.3-fold) in 10/76 liver samples (13%). This was fully accounted for by an intron 6 SNP (rs35599367, C>T), which also affected mRNA expression in cell culture on minigene transfections. CYP3A4 mRNA level and enzyme activity in livers with CC genotype were 1.7- and 2.5-fold, respectively, greater than in CT and TT carriers. In 235 patients taking stable doses of atorvastatin, simvastatin, or lovastatin for lipid control, carriers of the T allele required significantly lower statin doses (0.2-0.6-fold, P=0.019) than non-T carriers for optimal lipid control. These results indicate that intron 6 SNP rs35599367 markedly affects expression of CYP3A4 and could serve as a biomarker for predicting response to CYP3A4-metabolized drugs.

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Genetic variants of ACE are suspected risk factors in cardiovascular disease, but the alleles responsible for the variations remain unidentified. To search for regulatory polymorphisms, allelic angiotensin I-converting enzyme (ACE) mRNA expression was measured in 65 heart tissues, followed by genotype scanning of the ACE locus. Marked allelic expression imbalance (AEI) detected in five African-American subjects was associated with single-nucleotide polymorphisms (SNPs) (rs7213516, rs7214530, and rs4290) residing in conserved regions 2-3 kb upstream of ACE. Moreover, each of the SNPs affected transcription in reporter gene assays. SNPs rs4290 and rs7213516 were tested for associations with adverse cardiovascular outcomes in hypertensive patients with coronary disease (International Verapamil SR Trandolapril Study Genetic Substudy (INVEST-GENES), n = 1,032). Both SNPs were associated with adverse cardiovascular outcomes, largely attributable to nonfatal myocardial infarction in African Americans, showing an odds ratio of 6.16 (2.43-15.60) (P < 0.0001) for rs7213516. The high allele frequency in African Americans (16%) compared to Hispanics (4%) and Caucasians (<1%) suggests that these alleles contribute to variation between populations in cardiovascular risk and treatment outcomes.

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Tryptophan hydroxylase isoform 2 (TPH2) is expressed in serotonergic neurons in the raphe nuclei, where it catalyzes the rate-limiting step in the synthesis of the neurotransmitter serotonin. In search for functional polymorphisms within the TPH2 gene locus, we measured allele-specific expression of TPH2 mRNA in sections of human pons containing the dorsal and median raphe nuclei. Differences in allelic mRNA expression--referred to as allelic expression imbalance (AEI)--are a measure of cis-acting regulation of gene expression and mRNA processing. Two marker SNPs, located in exons 7 and 9 of TPH2 (rs7305115 and rs4290270, respectively), served for quantitative allelic mRNA measurements in pons RNA samples from 27 individuals heterozygous for one or both SNPs. Significant AEI (ranging from 1.2- to 2.5-fold) was detected in 19 out of the 27 samples, implying the presence of cis-acting polymorphisms that differentially affect TPH2 mRNA levels in pons. For individuals heterozygous for both marker SNPs, the results correlated well (r=0.93), validating the AEI analysis. AEI is tightly associated with the exon 7 marker SNP, in 17 of 18 subjects. Remarkably, expression from the minor allele exceeded that of the major allele in each case, possibly representing a gain-of-function. Genotyping of 20 additional TPH2 SNPs identified a haplotype block of five tightly linked SNPs for which heterozygosity is highly correlated with AEI and overall expression of TPH2 mRNA. These results reveal the presence of a functional cis-acting polymorphism, with high frequency in normal human subjects, resulting in increased TPH2 expression levels. The SNPs that correlate with AEI are closely linked to TPH2 SNPs previously shown to associate with major depression and suicide.

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An insertion/deletion polymorphism in the SERT linked promoter region (SERTLPR), previously reported to regulate mRNA expression in vitro, has been associated with mental disorders and response to psychotropic drugs. Contradictory evidence, however, has raised questions about the role of SERTLPR in regulating mRNA expression in vivo. We have used analysis of allelic expression imbalance (AEI) of SERT mRNA to assess quantitatively the contribution of SERTLPR to mRNA expression in human post-mortem pons tissue sections containing serotonergic neurons of the dorsal and median raphe nuclei. Any difference in the expression of one allele over the other indicates the presence of cis-acting elements that differentially affect transcription and/or mRNA processing and turnover. Using a marker SNP in the 3' untranslated region of SERT mRNA, statistically significant differences in allelic mRNA levels were detected in nine out of 29 samples heterozygous for the marker SNP. While the allelic expression differences were relatively small (15-25%), they could nevertheless be physiologically relevant. Although previous results had suggested that the long form of SERTLPR yields higher mRNA levels than the short form, we did not observe a correlation between SERTLPR and allelic expression ratios. Also in contrast to previous results, we found no correlation between SERTLPR and allelic expression ratios or SERT mRNA levels in B-lymphocytes. This study demonstrates that regulation of SERT mRNA is independent of SERTLPR, but could be associated with polymorphisms in partial linkage disequilibrium with SERTLPR.

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To facilitate a systematic study of chemoresistance across diverse classes of anticancer drug candidates, we performed correlation analyses between cytotoxic drug potency and gene expression in 60 tumor cell lines (NCI-60; NCI-National Cancer Institute). Ellipticine analogs displayed a range of correlation coefficients (r) with MDR1 (ABCB1, encoding multidrug resistance (MDR) protein MDR1 or P-glycoprotein). To determine MDR1 interactions of five ellipticines with diverse MDR1-r values, we employed MDR1-transport and cytotoxicity assays, using MDR1 inhibitors and siRNA-mediated MDR1 downregulation, in MDR1-overexpressing cells. Ellipticines with negative correlations-indicative of MDR1-mediated resistance-were shown to be MDR1 substrates, whereas those with neutral or positive correlations served as MDR1 inhibitors, which escape MDR1-mediated chemoresistance. Correlation with additional genes in the NCI-60 confirmed topoisomerases as ellipticine targets, but suggested distinct mechanisms of action and chemoresistance among them, providing a guide for selecting optimal drug candidates.

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A number of novel alpha-melanotropin (alpha-MSH) analogues have been designed, synthesized, and assayed for bioactivity at the melanocortin-1 (MC1) receptor from Xenopus frog skin, and selected potent analogues were examined at recombinant human MC1, MC3, and MC4 receptors expressed in human embryonic kidney (HEK) cells. These ligands were designed from Deltorphin-II, by a new hybrid approach, which incorporates the hydrophobic tail and the address sequence of Deltorphin-II (Glu-Val-Val-Gly-NH(2)) and key pharmacophore elements of melanotropins. Some of the ligands designed, c[Xxx-Yyy-Zzz-Arg-Trp-Glu]-Val-Val-Gly-NH(2) [XXX = nothing, Gly, beta-Ala, gamma-Abu, 6-Ahx; YYY = His, His(3-Bom), (S)-cyclopentylglycine (Cpg); ZZZ = Phe, d-Phe; d-Nal(2')], show high potency at melanocortin receptors. One ligand, GXH-32B-c[beta-Ala-His-d-Nal(2')-Arg-Trp-Glu]-Val-Val-Gly-NH(2), the most potent of the chimeric analogues tested, displayed agonist activity at each of the MC receptor subtypes analyzed, with an EC(50) of 2 nM at the amphibian MC1 receptor. In contrast, GXH-38B-c[Gly-Cpg-d-Nal(2')-Arg-Trp-Glu]-Val-Val-Gly-NH(2) (Cpg = cyclopentyl glycine) was an antagonist with a IC(50) of 43 nM at the amphibian receptor, and among the human subtypes tested, was the most potent at the MC1 receptor subtype where it also acted as an antagonist (K(i) = 53 nM), which is the first potent antagonist discovered for the human MC1 receptor. These results provide strong evidence supporting our hypothesis that ligand scaffolds for different G-protein coupled receptors (GPCRs) can be used to design ligands for other GPCRs and to design more potent ligands to treat diseases associated with the human MC1 receptor.

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Proton-coupled oligopeptide transporter PEPT1 facilitates the transport of dipeptides and peptoid drugs (including antibiotics) across the cell membranes of endothelial and epithelial cells. Substrate transport by the proton symport is driven by pH gradients, while the profile of pH sensitivity is regulated by a closely related protein, hPEPT1-RF. We investigated the genomic structure of hPEPT1 and hPEPT1-RF. Analysis of the high-throughput genomic sequence (HTGS) database revealed that hPEPT1 and hPEPT1-RF are splice variants encoded by the same gene located in chromosome 13, consisting of 24 exons. hPEPT1 is encoded by 23 exons and hPEPT1-RF by 6 exons. Coding sequences of hPEPT1-RF share 3 exons completely and 2 exons partially with hPEPT1. The genomic organization of hPEPT1 shows high similarity with its mouse orthologue. Exon-intron boundaries occur mostly in the loops connecting transmembrane segments (TMSs), suggesting a modular gene structure reflecting the TMS-loop repeat units in hPEPT1. The putative promoter region of hPEPT1 contains TATA boxes and GC-rich regions and a potential insulin responsive element.

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Guanine nucleotide-binding protein-coupled receptors (GPCRs) comprise large and diverse gene families in fungi, plants, and the animal kingdom. GPCRs appear to share a common structure with 7 transmembrane segments, but sequence similarity is minimal among the most distant GPCRs. To reevaluate the question of evolutionary relationships among the disparate GPCR families, this study takes advantage of the dramatically increased number of cloned GPCRs. Sequences were selected from the National Center for Biotechnology Information (NCBI) nonredundant peptide database using iterative BLAST (Basic Local Alignment Search Tool) searches to yield a database of approximately 1700 GPCRs and unrelated membrane proteins as controls, divided into 34 distinct clusters. For each cluster, separate position-specific matrices were established to optimize sequence comparisons among GPCRs. This approach resulted in significant alignments between distant GPCR families, including receptors for the biogenic amine/peptide, VIP/secretin, cAMP, STE3/MAP3 fungal pheromones, latrophilin, developmental receptors frizzled and smoothened, as well as the more distant metabotrobic glutamate receptors, the STE2/MAM2 fungal pheromone receptors, and GPR1, a fungal glucose receptor. On the other hand, alignment scores between these recognized GPCR clades with p40 (putative GPCR) and pm1 (putative GPCR), as well as bacteriorhodopsins, failed to support a finding of homology. This study provides a refined view of GPCR ancestry and serves as a reference database with hyperlinks to other sources. Moreover, it may facilitate database annotation and the assignment of orphan receptors to GPCR families.

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Numerous genes encode G protein-coupled receptors (GPCRs)-a main molecular target for drug therapy. Estimates indicate that the human genome contains approximately 600 GPCR genes. This article addresses therapeutic implications of sequence variations in GPCR genes. A number of inactivating and activating receptor mutations have been shown to cause a variety of (mostly rare) genetic disorders. However, pharmacogenetic and pharmacogenomic studies on GPCRs are scarce, and therapeutic relevance of variant receptor alleles often remains unclear. Confounding factors in assessing the therapeutic relevance of variant GPCR alleles include 1) interaction of a single drug with multiple closely related receptors, 2) poorly defined binding pockets that can accommodate drug ligands in different orientations or at alternative receptor domains, 3) possibility of multiple receptor conformations with distinct functions, and 4) multiple signaling pathways engaged by a single receptor. For example, antischizophrenic drugs bind to numerous receptors, several of which might be relevant to therapeutic outcome. Without knowing accurately what role a given receptor subtype plays in clinical outcome and how a sequence variation affects drug-induced signal transduction, we cannot predict the therapeutic relevance of a receptor variant. Genome-wide association studies with single nucleotide polymorphisms could identify critical target receptors for disease susceptibility and drug efficacy or toxicity.

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CONTEXT: Adverse drug reactions are a significant cause of morbidity and mortality. Although many adverse drug reactions are considered nonpreventable, recent developments suggest these reactions may be avoided through individualization of drug therapies based on genetic information, an application known as pharmacogenomics. OBJECTIVE: To evaluate the potential role of pharmacogenomics in reducing the incidence of adverse drug reactions. DATA SOURCES: MEDLINE English-language only searches for adverse drug reaction studies published between January 1995 and June 2000 and review articles of variant alleles of drug-metabolizing enzymes published between January 1997 and August 2000. We also used online resources, texts, and expert opinion. STUDY SELECTION: Detailed inclusion criteria were used to select studies. We included 18 of 333 adverse drug reaction studies and 22 of 61 variant allele review articles. DATA EXTRACTION: All the investigators reviewed and coded articles using standardized abstracting forms. DATA SYNTHESIS: We identified 27 drugs frequently cited in adverse drug reaction studies. Among these drugs, 59% are metabolized by at least 1 enzyme with a variant allele known to cause poor metabolism. Conversely, only 7% to 22% of randomly selected drugs are known to be metabolized by enzymes with this genetic variability (range, P =.006-P<.001). CONCLUSIONS: Our results suggest that drug therapy based on individuals' genetic makeups may result in a clinically important reduction in adverse outcomes. Our findings serve as a foundation for further research on how pharmacogenomics can reduce the incidence of adverse reactions and on the resulting clinical, societal, and economic implications.

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