Browse
Submit Data
Databases
API
Help

Dataset Information

10 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Role of Adenylate Cyclase 9 in the Pharmacogenomic Response to Dalcetrapib: Clinical Paradigm and Molecular Mechanisms in Precision Cardiovascular Medicine.

ABSTRACT: Following the neutral results of the dal-OUTCOMES trial, a genome-wide study identified the rs1967309 variant in the adenylate cyclase type 9 (ADCY9) gene on chromosome 16 as being associated with the risk of future cardiovascular events only in subjects taking dalcetrapib, a CETP (cholesterol ester transfer protein) modulator. Homozygotes for the minor A allele (AA) were protected from recurrent cardiovascular events when treated with dalcetrapib, while homozygotes for the major G allele (GG) had increased risk. Here, we present the current state of knowledge regarding the impact of rs1967309 in ADCY9 on clinical observations and biomarkers in dalcetrapib trials and the effects of mouse ADCY9 gene inactivation on cardiovascular physiology. Finally, we present our current model of the interaction between dalcetrapib and ADCY9 gene variants in the arterial wall macrophage, based on the intracellular role of CETP in the transfer of complex lipids from endoplasmic reticulum membranes to lipid droplets. Briefly, the concept is that dalcetrapib would inhibit CETP-mediated transfer of cholesteryl esters, resulting in a progressive inhibition of cholesteryl ester synthesis and free cholesterol accumulation in the endoplasmic reticulum. Reduced ADCY9 activity, by paradoxically leading to higher cyclic AMP levels and in turn increased cellular cholesterol efflux, could impart cardiovascular protection in rs1967309 AA patients. The ongoing dal-GenE trial recruited 6145 patients with the protective AA genotype and will provide a definitive answer to whether dalcetrapib will be protective in this population.

SUBMITTER: Rhainds D

PROVIDER: S-EPMC8284386 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Pharmacogenomic Impact of CYP2C19 Variation on Clopidogrel Therapy in Precision Cardiovascular Medicine.

Project description:Variability in response to antiplatelet therapy can be explained in part by pharmacogenomics, particularly of the CYP450 enzyme encoded by CYP2C19. Loss-of-function and gain-of-function variants help explain these interindividual differences. Individuals may carry multiple variants, with linkage disequilibrium noted among some alleles. In the current pharmacogenomics era, genomic variation in CYP2C19 has led to the definition of pharmacokinetic phenotypes for response to antiplatelet therapy, in particular, clopidogrel. Individuals may be classified as poor, intermediate, extensive, or ultrarapid metabolizers, based on whether they carry wild type or polymorphic CYP2C19 alleles. Variant alleles differentially impact platelet reactivity, concentration of plasma clopidogrel metabolites, and clinical outcomes. Interestingly, response to clopidogrel appears to be modulated by additional factors, such as sociodemographic characteristics, risk factors for ischemic heart disease, and drug-drug interactions. Furthermore, systems medicine studies suggest that a broader approach may be required to adequately assess, predict, preempt, and manage variation in antiplatelet response. Transcriptomics, epigenomics, exposomics, miRNAomics, proteomics, metabolomics, microbiomics, and mathematical, computational, and molecular modeling should be integrated with pharmacogenomics for enhanced prediction and individualized care. In this review of pharmacogenomic variation of CYP450, a systems medicine approach is described for tailoring antiplatelet therapy in clinical practice of precision cardiovascular medicine.

| S-EPMC5872082 | biostudies-literature

Emerging Role of Precision Medicine in Cardiovascular Disease.

Project description:Precision medicine is an integrative approach to cardiovascular disease prevention and treatment that considers an individual's genetics, lifestyle, and exposures as determinants of their cardiovascular health and disease phenotypes. This focus overcomes the limitations of reductionism in medicine, which presumes that all patients with the same signs of disease share a common pathophenotype and, therefore, should be treated similarly. Precision medicine incorporates standard clinical and health record data with advanced panomics (ie, transcriptomics, epigenomics, proteomics, metabolomics, and microbiomics) for deep phenotyping. These phenotypic data can then be analyzed within the framework of molecular interaction (interactome) networks to uncover previously unrecognized disease phenotypes and relationships between diseases, and to select pharmacotherapeutics or identify potential protein-drug or drug-drug interactions. In this review, we discuss the current spectrum of cardiovascular health and disease, population averages and the response of extreme phenotypes to interventions, and population-based versus high-risk treatment strategies as a pretext to understanding a precision medicine approach to cardiovascular disease prevention and therapeutic interventions. We also consider the search for resilience and Mendelian disease genes and argue against the theory of a single causal gene/gene product as a mediator of the cardiovascular disease phenotype, as well as an Erlichian magic bullet to solve cardiovascular disease. Finally, we detail the importance of deep phenotyping and interactome networks and the use of this information for rational polypharmacy. These topics highlight the urgent need for precise phenotyping to advance precision medicine as a strategy to improve cardiovascular health and prevent disease.

| S-EPMC6021027 | biostudies-literature

RNA Therapeutics in Cardiovascular Precision Medicine.

Project description:Since our knowledge on structure and function of messenger RNA (mRNA) has expanded from merely being an intermediate molecule between DNA and proteins to the notion that RNA is a dynamic gene regulator that can be modified and edited, RNA has become a focus of interest into developing novel therapeutic schemes. Therapeutic modulation of RNA molecules by DNA- and RNA-based therapies has broadened the scope of therapeutic targets in infectious diseases, cancer, neurodegenerative diseases and most recently in cardiovascular diseases as well. Currently, antisense oligonucleotides (ASO), small interfering RNAs (siRNAs), and microRNAs are the most widely applied therapeutic strategies to target RNA molecules and regulate gene expression and protein production. However, a number of barriers have to be overcome including instability, inadequate binding affinity and delivery to the tissues, immunogenicity, and off-target toxicity in order for these agents to evolve into efficient drugs. As cardiovascular diseases remain the leading cause of mortality worldwide, a large number of clinical trials are under development investigating the safety and efficacy of RNA therapeutics in clinical conditions such as familial hypercholesterolemia, diabetes mellitus, hypertriglyceridemia, cardiac amyloidosis, and atrial fibrillation. In this review, we summarize the clinical trials of RNA-targeting therapies in cardiovascular disease and critically discuss the advances, the outcomes, the limitations and the future directions of RNA therapeutics in precision transcriptomic medicine.

| S-EPMC6068259 | biostudies-literature

Mechanisms mediating pituitary adenylate cyclase-activating polypeptide depolarization of rat sympathetic neurons.

Project description:The direct effects of pituitary adenylate cyclase-activating polypeptides (PACAP) on sympathetic neurons were investigated using rat superior cervical ganglion neurons. Electrophysiological and pharmacological analyses were used to evaluate PACAP modulation of sympathetic neuron membrane potentials and to investigate potential ionic and intracellular signaling mechanisms mediating the responses. More than 90% of the sympathetic neurons were depolarized by the PACAP peptides even when stimulated release was blocked, indicating that the PACAP peptides elicited primary responses in the postganglionic neurons. The response profile was consistent for activation of PACAP-selective PAC(1) receptors: nanomolar concentrations of PACAP27 and PACAP38 were required to stimulate depolarization, whereas vasoactive intestinal peptide failed to evoke any response. Furthermore, depolarizations elicited by PACAP27 were reduced by the PAC(1) receptor antagonist PACAP(6-38). Both sodium influx and inhibition of a potassium current contributed to the peptide-induced depolarizations. Activation of neither pertussis toxin- nor cholera toxin-sensitive G-proteins was required for generation of the depolarizations. cAMP and diacylglycerol production and activation of protein kinase A or protein kinase C also were not requisite for the responses. By contrast, phospholipase C (PLC)-dependent inositol 1,4,5-triphosphate (IP(3)) synthesis was crucial to the PACAP-mediated depolarizations. Although calcium release from IP(3)-sensitive stores was not required for the PACAP-induced responses, inhibition of IP(3) receptors reduced the depolarizations. Thus, among the many signal transduction pathways coupled to the PAC(1) receptor, the PACAP-induced depolarization of sympathetic neurons appears to require activation of PLC and subsequent generation of IP(3).

| S-EPMC6772758 | biostudies-literature

Global Text Mining and Development of Pharmacogenomic Knowledge Resource for Precision Medicine.

Project description:Understanding patients' genomic variations and their effect in protecting or predisposing them to drug response phenotypes is important for providing personalized healthcare. Several studies have manually curated such genotype-phenotype relationships into organized databases from clinical trial data or published literature. However, there are no text mining tools available to extract high-accuracy information from such existing knowledge. In this work, we used a semiautomated text mining approach to retrieve a complete pharmacogenomic (PGx) resource integrating disease-drug-gene-polymorphism relationships to derive a global perspective for ease in therapeutic approaches. We used an R package, pubmed.mineR, to automatically retrieve PGx-related literature. We identified 1,753 disease types, and 666 drugs, associated with 4,132 genes and 33,942 polymorphisms collated from 180,088 publications. With further manual curation, we obtained a total of 2,304 PGx relationships. We evaluated our approach by performance (precision = 0.806) with benchmark datasets like Pharmacogenomic Knowledgebase (PharmGKB) (0.904), Online Mendelian Inheritance in Man (OMIM) (0.600), and The Comparative Toxicogenomics Database (CTD) (0.729). We validated our study by comparing our results with 362 commercially used the US- Food and drug administration (FDA)-approved drug labeling biomarkers. Of the 2,304 PGx relationships identified, 127 belonged to the FDA list of 362 approved pharmacogenomic markers, indicating that our semiautomated text mining approach may reveal significant PGx information with markers for drug response prediction. In addition, it is a scalable and state-of-art approach in curation for PGx clinical utility.

| S-EPMC6692532 | biostudies-literature

Precision Medicine in Neurology: The Inspirational Paradigm of Complement Therapeutics.

Project description:Precision medicine has emerged as a central element of healthcare science. Complement, a component of innate immunity known for centuries, has been implicated in the pathophysiology of numerous incurable neurological diseases, emerging as a potential therapeutic target and predictive biomarker. In parallel, the innovative application of the first complement inhibitor in clinical practice as an approved treatment of myasthenia gravis (MG) and neuromyelitis optica spectrum disorders (NMOSD) related with specific antibodies raised hope for the implementation of personalized therapies in detrimental neurological diseases. A thorough literature search was conducted through May 2020 at MEDLINE, EMBASE, Cochrane Library and ClinicalTrials.gov databases based on medical terms (MeSH)" complement system proteins" and "neurologic disease". Complement's role in pathophysiology, monitoring of disease activity and therapy has been investigated in MG, multiple sclerosis, NMOSD, spinal muscular atrophy, amyotrophic lateral sclerosis, Parkinson, Alzheimer, Huntington disease, Guillain-Barré syndrome, chronic inflammatory demyelinating polyneuropathy, stroke, and epilepsy. Given the complexity of complement diagnostics and therapeutics, this state-of-the-art review aims to provide a brief description of the complement system for the neurologist, an overview of novel complement inhibitors and updates of complement studies in a wide range of neurological disorders.

| S-EPMC7693884 | biostudies-literature

Review of precision cancer medicine: Evolution of the treatment paradigm.

Project description:In recent years, biotechnological breakthroughs have led to identification of complex and unique biologic features associated with carcinogenesis. Tumor and cell-free DNA profiling, immune markers, and proteomic and RNA analyses are used to identify these characteristics for optimization of anticancer therapy in individual patients. Consequently, clinical trials have evolved, shifting from tumor type-centered to gene-directed, histology-agnostic, with innovative adaptive design tailored to biomarker profiling with the goal to improve treatment outcomes. A plethora of precision medicine trials have been conducted. The majority of these trials demonstrated that matched therapy is associated with superior outcomes compared to non-matched therapy across tumor types and in specific cancers. To improve the implementation of precision medicine, this approach should be used early in the course of the disease, and patients should have complete tumor profiling and access to effective matched therapy. To overcome the complexity of tumor biology, clinical trials with combinations of gene-targeted therapy with immune-targeted approaches (e.g., checkpoint blockade, personalized vaccines and/or chimeric antigen receptor T-cells), hormonal therapy, chemotherapy and/or novel agents should be considered. These studies should target dynamic changes in tumor biologic abnormalities, eliminating minimal residual disease, and eradicating significant subclones that confer resistance to treatment. Mining and expansion of real-world data, facilitated by the use of advanced computer data processing capabilities, may contribute to validation of information to predict new applications for medicines. In this review, we summarize the clinical trials and discuss challenges and opportunities to accelerate the implementation of precision oncology.

| S-EPMC7272286 | biostudies-literature

Precision Cardiovascular Medicine: State of Genetic Testing.

Project description:In the 15 years following the release of the first complete human genome sequences, our understanding of rare and common genetic variation as determinants of cardiovascular disease susceptibility, prognosis, and therapeutic response has grown exponentially. As such, the use of genomics to enhance the care of patients with cardiovascular diseases has garnered increased attention from clinicians, researchers, and regulatory agencies eager to realize the promise of precision genomic medicine. However, owing to a large burden of "complex" common diseases, emphasis on evidence-based practice, and a degree of unfamiliarity/discomfort with the language of genomic medicine, the development and implementation of genomics-guided approaches designed to further individualize the clinical management of a variety of cardiovascular disorders remains a challenge. In this review, we detail a practical approach to genetic testing initiation and interpretation as well as review the current state of cardiovascular genetic and pharmacogenomic testing in the context of relevant society and regulatory agency recommendations/guidelines.

| S-EPMC6364981 | biostudies-literature

DMET™ (Drug Metabolism Enzymes and Transporters): a pharmacogenomic platform for precision medicine.

Project description:In the era of personalized medicine, high-throughput technologies have allowed the investigation of genetic variations underlying the inter-individual variability in drug pharmacokinetics/pharmacodynamics. Several studies have recently moved from a candidate gene-based pharmacogenetic approach to genome-wide pharmacogenomic analyses to identify biomarkers for selection of patient-tailored therapies. In this aim, the identification of genetic variants affecting the individual drug metabolism is relevant for the definition of more active and less toxic treatments. This review focuses on the potentiality, reliability and limitations of the DMET™ (Drug Metabolism Enzymes and Transporters) Plus as pharmacogenomic drug metabolism multi-gene panel platform for selecting biomarkers in the final aim to optimize drugs use and characterize the individual genetic background.

| S-EPMC5288240 | biostudies-literature

Corrigendum: Global Text Mining and Development of Pharmacogenomic Knowledge Resource for Precision Medicine.

Project description:[This corrects the article DOI: 10.3389/fphar.2019.00839.].

| S-EPMC7746840 | biostudies-literature