The clinical pharmacogenetics implementation consortium guideline for SLCO1B1 and simvastatin-induced myopathy: 2014 update.

Simvastatin is among the most commonly used prescription medications for cholesterol reduction. A single coding single-nucleotide polymorphism, rs4149056T>C, in SLCO1B1 increases systemic exposure to simvastatin and the risk of muscle toxicity. We summarize evidence from the literature supporting this association and provide therapeutic recommendations for simvastatin based on SLCO1B1 genotype. This article is an update to the 2012 Clinical Pharmacogenetics Implementation Consortium guideline for SLCO1B1 and simvastatin-induced myopathy.

Characterization of statin dose response in electronic medical records.

Efforts to define the genetic architecture underlying variable statin response have met with limited success, possibly because previous studies were limited to effect based on a single dose. We leveraged electronic medical records (EMRs) to extract potency (ED50) and efficacy (Emax) of statin dose-response curves and tested them for association with 144 preselected variants. Two large biobanks were used to construct dose-response curves for 2,026 and 2,252 subjects on simvastatin and atorvastatin, respectively. Atorvastatin was more efficacious, was more potent, and demonstrated less interindividual variability than simvastatin. A pharmacodynamic variant emerging from randomized trials (PRDM16) was associated with Emax for both. For atorvastatin, Emax was 51.7 mg/dl in subjects homozygous for the minor allele vs. 75.0 mg/dl for those homozygous for the major allele. We also identified several loci associated with ED50. The extraction of rigorously defined traits from EMRs for pharmacogenetic studies represents a promising approach to further understand the genetic factors contributing to drug response.

A common functional promoter variant links CNR1 gene expression to HDL cholesterol level.

Type 1 cannabinoid receptor blockers increase high-density lipoprotein cholesterol levels. Although genetic variation in the type 1 cannabinoid receptor--encoded by the CNR1 gene--is known to influence high-density lipoprotein cholesterol level as well, human studies conducted to date have been limited to genetic markers such as haplotype-tagging single nucleotide polymorphisms. Here we identify rs806371 in the CNR1 promoter as the causal variant. We re-sequence the CNR1 gene and genotype all variants in a DNA biobank linked to comprehensive electronic medical records. By testing each variant for association with high-density lipoprotein cholesterol level in a clinical practice-based setting, we localize a putative functional allele to a 100-bp window in the 5'-flanking region. Assessment of variants in this window for functional impact on electrophoretic mobility shift assay identifies rs806371 as a novel regulatory binding element. Reporter gene assays confirm that rs806371 reduces gene expression, thereby linking CNR1 gene variation to high-density lipoprotein cholesterol level in humans.

CYP4A11 variant is associated with high-density lipoprotein cholesterol in women.

The ω-hydroxylase CYP4A11 catalyzes the transformation of epoxyeicosatrienoic acids (EETs) to ω-hydroxylated EETs, endogenous peroxisome proliferator-activated receptor-α (PPARα) agonists. PPARα activation increases high-density lipoprotein cholesterol (HDL-C). A cytosine-for-thymidine (T8590C) variant of CYP4A11 encodes for an ω-hydroxylase with reduced activity. This study examined the relationship between CYP4A11 T8590C genotype and metabolic parameters in the Framingham Offspring Study and in a clinical practice-based biobank, BioVU. In women in the Framingham Offspring Study, the CYP4A11 8590C allele was associated with reduced HDL-C concentrations (52.1±0.5 mg dl(-1) in CYP4A11 CC- or CT-genotype women versus 54.8±0.5 mg dl(-1) in TT women at visit 2, P=0.02), and with an increased prevalence of low HDL-C, defined categorically as 50 mg dl(-1) (odds ratio 1.39 (95% CI 1.02-1.90), P=0.04). In the BioVU cohort, the CYP4A11 8590C allele was also associated with low HDL-C in women (odds ratio 1.69 (95% CI 1.03-2.77, P=0.04)). There was no relationship between genotype and HDL-C in men in either cohort.

The effect of novel promoter variants in MATE1 and MATE2 on the pharmacokinetics and pharmacodynamics of metformin.

Interindividual variation in response to metformin, first-line therapy for type 2 diabetes, is substantial. Given that transporters are determinants of metformin pharmacokinetics, we examined the effects of promoter variants in both multidrug and toxin extrusion protein 1 (MATE1) (g.-66T → C, rs2252281) and MATE2 (g.-130G → A, rs12943590) on variation in metformin disposition and response. The pharmacokinetics and glucose-lowering effects of metformin were assessed in healthy volunteers (n = 57) receiving metformin. The renal and secretory clearances of metformin were higher (22% and 26%, respectively) in carriers of variant MATE2 who were also MATE1 reference (P < 0.05). Both MATE genotypes were associated with altered post-metformin glucose tolerance, with variant carriers of MATE1 and MATE2 having an enhanced (P < 0.01) and reduced (P < 0.05) response, respectively. Consistent with these results, patients with diabetes (n = 145) carrying the MATE1 variant showed enhanced metformin response. These findings suggest that promoter variants of MATE1 and MATE2 are important determinants of metformin disposition and response in healthy volunteers and diabetic patients.

Optimizing drug outcomes through pharmacogenetics: a case for preemptive genotyping.

Routine integration of genotype data into drug decision making could improve patient safety, particularly if many relevant genetic variants can be assayed simultaneously before prescribing the target drug. The frequency of opportunities for pharmacogenetic prescribing and the potential adverse events (AEs) mitigated are unknown. We examined the frequency with which 56 medications with known outcomes influenced by variant alleles were prescribed in a cohort of 52,942 medical home patients at Vanderbilt University Medical Center (VUMC). Within a 5-year window, we estimated that 64.8% (95% confidence interval (CI): 64.4-65.2%) of individuals were exposed to at least one medication with an established pharmacogenetic association. Using previously published results for six medications with severe, well-characterized, genetically linked AEs, we estimated that 383 events (95% CI, 212-552) could have been prevented with an effective preemptive genotyping program. Our results suggest that multiplexed, preemptive genotyping may represent an efficient alternative approach to current single-use ("reactive") methods and may also improve safety.

The clinical pharmacogenomics implementation consortium: CPIC guideline for SLCO1B1 and simvastatin-induced myopathy.

Cholesterol reduction from statin therapy has been one of the greatest public health successes in modern medicine. Simvastatin is among the most commonly used prescription medications. A non-synonymous coding single-nucleotide polymorphism (SNP), rs4149056, in SLCO1B1 markedly increases systemic exposure to simvastatin and the risk of muscle toxicity. This guideline explores the relationship between rs4149056 (c.521T>C, p.V174A) and clinical outcome for all statins. The strength of the evidence is high for myopathy with simvastatin. We limit our recommendations accordingly.

Operational implementation of prospective genotyping for personalized medicine: the design of the Vanderbilt PREDICT project.

The promise of "personalized medicine" guided by an understanding of each individual's genome has been fostered by increasingly powerful and economical methods to acquire clinically relevant information. We describe the operational implementation of prospective genotyping linked to an advanced clinical decision-support system to guide individualized health care in a large academic health center. This approach to personalized medicine entails engagement between patient and health-care provider, identification of relevant genetic variations for implementation, assay reliability, point-of-care decision support, and necessary institutional investments. In one year, approximately 3,000 patients, most of whom were scheduled for cardiac catheterization, were genotyped on a multiplexed platform that included genotyping for CYP2C19 variants that modulate response to the widely used antiplatelet drug clopidogrel. These data are deposited into the electronic medical record (EMR), and point-of-care decision support is deployed when clopidogrel is prescribed for those with variant genotypes. The establishment of programs such as this is a first step toward implementing and evaluating strategies for personalized medicine.

Electronic medical records as a tool in clinical pharmacology: opportunities and challenges.

The development and increasing sophistication of electronic medical record (EMR) systems hold the promise of not only improving patient care but also providing unprecedented opportunities for discovery in the fields of basic, translational, and implementation sciences. Clinical pharmacology research in the EMR environment has only recently started to become a reality, with EMRs becoming increasingly populated, methods to mine drug response and other phenotypes becoming more sophisticated, and links being established with DNA repositories.

A common 5'-UTR variant in MATE2-K is associated with poor response to metformin.

Multidrug and toxin extrusion 2 (MATE2-K (SLC47A2)), a polyspecific organic cation exporter, facilitates the renal elimination of the antidiabetes drug metformin. In this study, we characterized genetic variants of MATE2-K, determined their association with metformin response, and elucidated their impact by means of a comparative protein structure model. Four nonsynonymous variants and four variants in the MATE2-K basal promoter region were identified from ethnically diverse populations. Two nonsynonymous variants-c.485C>T and c.1177G>A-were shown to be associated with significantly lower metformin uptake and reduction in protein expression levels. MATE2-K basal promoter haplotypes containing the most common variant, g.-130G>A (>26% allele frequency), were associated with a significant increase in luciferase activities and reduced binding to the transcriptional repressor myeloid zinc finger 1 (MZF-1). Patients with diabetes who were homozygous for g.-130A had a significantly poorer response to metformin treatment, assessed as relative change in glycated hemoglobin (HbA1c) (-0.027 (-0.076, 0.033)), as compared with carriers of the reference allele, g.-130G (-0.15 (-0.17, -0.13)) (P=0.002). Our study showed that MATE2-K plays a role in the antidiabetes response to metformin.

Case definition and phenotype standardization in drug-induced liver injury.

Drug-induced liver injury (DILI) is the most frequent reason cited for the withdrawal of approved drugs from the market and accounts for up to 15% of the cases of acute liver failure. Investigators around the globe have begun to identify and study patients with DILI; several large registries and tissue banks are being established. In order to gain the maximum scientific benefit from these efforts, the definitions and terminology related to the clinical phenotypes of DILI must be harmonized. For this purpose, an international DILI Expert Working Group of clinicians and scientists reviewed current DILI terminology and diagnostic criteria so as to develop more uniform criteria that would define and characterize the spectrum of clinical syndromes that constitute DILI. Consensus was established with respect to the threshold criteria for definition of a case as being DILI, the pattern of liver injury, causality assessment, severity, and chronicity. Consensus was also reached on approaches to characterizing DILI in the setting of chronic liver diseases, including autoimmune hepatitis (AIH).

The emerging role of electronic medical records in pharmacogenomics.

Health-care information technology and genotyping technology are both advancing rapidly, creating new opportunities for medical and scientific discovery. The convergence of these two technologies is now facilitating genetic association studies of unprecedented size within the context of routine clinical care. As a result, the medical community will soon be presented with a number of novel opportunities to bring functional genomics to the bedside in the area of pharmacotherapy. By linking biological material to comprehensive medical records, large multi-institutional biobanks are now poised to advance the field of pharmacogenomics through three distinct mechanisms: (i) retrospective assessment of previously known findings in a clinical practice-based setting, (ii) discovery of new associations in huge observational cohorts, and (iii) prospective application in a setting capable of providing real-time decision support. This review explores each of these translational mechanisms within a historical framework.

High-density lipoprotein (HDL) cholesterol: leveraging practice-based biobank cohorts to characterize clinical and genetic predictors of treatment outcome.

Over the past decade, large multicenter trials have unequivocally demonstrated that decreasing low-density lipoprotein (LDL) cholesterol can reduce both primary and secondary cardiovascular events in patients at risk. However, even in the context of maximal LDL lowering, there remains considerable residual cardiovascular risk. Some of this risk can be attributed to variability in high-density lipoprotein (HDL) cholesterol. As such, there is tremendous interest in defining determinants of HDL homeostasis. Risk prediction models are being constructed based upon (1) clinical contributors, (2) known molecular determinants and (3) the genetic architecture underlying HDL cholesterol levels. To date, however, no single resource has combined these factors within the context of a practice-based data set. Recently, a number of academic medical centers have begun constructing DNA biobanks linked to secure encrypted versions of their respective electronic medical record. As these biobanks combine resources, the clinical community is in a position to characterize lipid-related treatment outcome on an unprecedented scale.

Mapping genes that predict treatment outcome in admixed populations.

There is great interest in characterizing the genetic architecture underlying drug response. For many drugs, gene-based dosing models explain a considerable amount of the overall variation in treatment outcome. As such, prescription drug labels are increasingly being modified to contain pharmacogenetic information. Genetic data must, however, be interpreted within the context of relevant clinical covariates. Even the most predictive models improve with the addition of data related to biogeographical ancestry. The current review explores analytical strategies that leverage population structure to more fully characterize genetic determinants of outcome in large clinical practice-based cohorts. The success of this approach will depend upon several key factors: (1) the availability of outcome data from groups of admixed individuals (that is, populations recombined over multiple generations), (2) a measurable difference in treatment outcome (that is, efficacy and toxicity end points), and (3) a measurable difference in allele frequency between the ancestral populations.

The Pathway Less Traveled: Moving from Candidate Genes to Candidate Pathways in the Analysis of Genome-Wide Data from Large Scale Pharmacogenetic Association Studies.

The candidate gene approach to pharmacogenetics is hypothesis driven, and anchored in biological plausibility. Whole genome scanning is hypothesis generating, and it may lead to new biology. While both approaches are important, the scientific community is rapidly reallocating resources toward the latter. We propose a step-wise approach to large-scale pharmacogenetic association studies that begins with candidate genes, then uses a pathway-based intermediate step, to inform subsequent analyses of data generated through whole genome scanning. Novel computational strategies are explored in the context of two clinically relevant examples, cholesterol synthesis and lipid signaling.

Healthy People 2010 disease prevalence in the Marshfield Clinic Personalized Medicine Research Project cohort: opportunities for public health genomic research.

OBJECTIVES: The purpose of this study was to estimate the prevalence of Healthy People 2010 disease conditions in a large population-based cohort in central Wisconsin (WI, USA) and to consider how these conditions can be prioritized for research based on the use of healthcare services, the prevalence of various disease states and the resulting study power. METHODS: Healthy People 2010 diagnoses were estimated for participants in the Personalized Medicine Research Project (PMRP), a large population-based biobank for residents aged 18 years and older living in central Wisconsin. By interrogating the electronic medical record, three parameters were calculated for each diagnosis: mean number of concomitant diagnoses, mean number of annual clinic visits before diagnosis and mean number of clinic visits after diagnosis. RESULTS: A total of 18,239 adults enrolled in PMRP from September 2002 to May 2005 and were included in the study. They had a mean age of 49 years (standard deviation: 18.5), ranging from 18-98 years; 57% were female. At least one Healthy People 2010 disease was diagnosed in 86.4% of the participants; 13.6% had never been diagnosed with any of these conditions. The median number of diagnoses per subject was three (range: 1-15). The median number of annual visits after diagnosis was lowest for chronic obstructive pulmonary disease (9.1) and highest for sleep apnea (17.9). Subjects with a diabetic retinopathy diagnosis had the highest number of concomitant diagnoses (mean: 6.8). DISCUSSION: All of the diseases within the Healthy People 2010 list are purported to have at least some genetic component, with the exception of injuries. The PMRP cohort is large enough that diseases of public health importance can be studied in the context of a variety of clinical and environmental covariates. This database is being developed as a national resource and is particularly useful where the estimated disease prevalence is 5% or greater. For less common diseases, additional cases can be recruited from throughout the Marshfield Clinic system of care, with population-based controls selected from the main PMRP study cohort.

Membrane-delimited coupling between sigma receptors and K+ channels in rat neurohypophysial terminals requires neither G-protein nor ATP.

Receptor-mediated modulation of ion channels generally involves G-proteins, phosphorylation, or both in combination. The sigma receptor, which modulates voltage-gated K+ channels, is a novel protein with no homology to other receptors known to modulate ion channels. In the present study patch clamp and photolabelling techniques were used to investigate the mechanism by which sigma receptors modulate K+ channels in peptidergic nerve terminals. The sigma receptor photoprobe iodoazidococaine labelled a protein with the same molecular mass (26 kDa) as the sigma receptor protein identified by cloning. The sigma receptor ligands pentazocine and SKF10047 modulated K+ channels, despite intra-terminal perfusion with GTP-free solutions, a G-protein inhibitor (GDPbetaS), a G-protein activator (GTPgammaS) or a non-hydrolysable ATP analogue (AMPPcP). Channels in excised outside-out patches were modulated by ligand, indicating that soluble cytoplasmic factors are not required. In contrast, channels within cell-attached patches were not modulated by ligand outside a patch, indicating that receptors and channels must be in close proximity for functional interactions. Channels expressed in oocytes without receptors were unresponsive to sigma receptor agonists, ruling out inhibition through a direct drug interaction with channels. These experiments indicate that sigma receptor-mediated signal transduction is membrane delimited, and requires neither G-protein activation nor protein phosphorylation. This novel transduction mechanism is mediated by membrane proteins in close proximity, possibly through direct interactions between the receptor and channel. This would allow for more rapid signal transduction than other ion channel modulation mechanisms, which in the present case of neurohypophysial nerve terminals would lead to the enhancement of neuropeptide release.

Accessory spleens in the thoracic and abdominal cavities after a relapse of idiopathic thrombocytopenic purpura: a case report.

This case report presents a highly unusual finding of ectopic splenic tissue in both the thoracic and abdominal cavities in a patient with recurrent idiopathic thrombocytopenic purpura (ITP).

Novel human TEF-1 isoforms exhibit altered DNA binding and functional properties.

The transcriptional enhancer factor-1 (TEF-1) is a member of the TEA/ATTS domain family. TEF-1 binds to GT-IIC (GGAATG), SphI (AGTATG), SphII (AGCATG), and M-CAT (GGTATG) response elements and is involved in the transactivation of a variety of genes, including the SV40 large T antigen, mammalian muscle-specific genes, and human chorionic somatomammotropin genes. Also, TEF-1 acts as a transcriptional repressor in placental cells, possibly through interaction with the TATA binding protein (TBP), preventing TBP binding to the TATA box. Here we describe the cloning, tissue-specific expression pattern, and functional characterization of two novel TEF-1 isoforms, TEF-1beta and TEF-1gamma. These isoforms most likely arise from alternative splicing of mRNA transcribed from a single gene and involve substitutions and/or insertions in a region immediately following the DNA binding domain. TEF-1beta appears to be widely distributed like the prototypic TEF-1, designated TEF-1alpha, whereas TEF-1gamma exhibits a narrower tissue-specific expression pattern that includes pancreas, kidney, and skeletal and heart muscle. The relatively limited sequence alterations among these isoforms cause significant changes in their DNA binding and transcriptional activities. TEF-1beta and TEF-1gamma bind to GT-IIC sequences with higher affinity and repress hCS promoter more efficiently than TEF-1alpha. These results suggest that each TEF-1 isoform may play unique regulatory roles in various tissues.