Pharmacogenomics in pain treatment.

Drug Metab Pers Ther. 2016 Sep 1;31(3):131-142

Authors: Peiró AM, Planelles B, Juhasz G, Bagdy G, Libert F, Eschalier A, Busserolles J, Sperlagh B, Llerena A

Abstract
The experience of chronic pain is one of the commonest reasons for seeking medical attention, being a major issue in clinical practice. While pain is a universal experience, only a small proportion of people who felt pain develop pain syndromes. In addition, painkillers are associated with wide inter-individual variability in the analgesic response. This may be partly explained by the presence of single nucleotide polymorphisms in genes encoding molecular entities involved in pharmacodynamics and pharmacokinetics. However, uptake of this information has been slow due in large part to the lack of robust evidences demonstrating clinical utility. Furthermore, novel therapies, including targeting of epigenetic changes and gene therapy-based approaches are further broadening future options for the treatment of chronic pain. The aim of this article is to review the evidences behind pharmacogenetics (PGx) to individualize therapy (boosting the efficacy and minimizing potential toxicity) and genes implicated in pain medicine, in two parts: (i) genetic variability with pain sensitivity and analgesic response; and (ii) pharmacological concepts applied on PGx.

PMID: 27662648 [PubMed - as supplied by publisher]

From Metabonomics to Pharmacometabonomics: The Role of Metabolic Profiling in Personalized Medicine.

Front Pharmacol. 2016;7:297

Authors: Everett JR

Abstract
Variable patient responses to drugs are a key issue for medicine and for drug discovery and development. Personalized medicine, that is the selection of medicines for subgroups of patients so as to maximize drug efficacy and minimize toxicity, is a key goal of twenty-first century healthcare. Currently, most personalized medicine paradigms rely on clinical judgment based on the patient's history, and on the analysis of the patients' genome to predict drug effects i.e., pharmacogenomics. However, variability in patient responses to drugs is dependent upon many environmental factors to which human genomics is essentially blind. A new paradigm for predicting drug responses based on individual pre-dose metabolite profiles has emerged in the past decade: pharmacometabonomics, which is defined as "the prediction of the outcome (for example, efficacy or toxicity) of a drug or xenobiotic intervention in an individual based on a mathematical model of pre-intervention metabolite signatures." The new pharmacometabonomics paradigm is complementary to pharmacogenomics but has the advantage of being sensitive to environmental as well as genomic factors. This review will chart the discovery and development of pharmacometabonomics, and provide examples of its current utility and possible future developments.

PMID: 27660611 [PubMed]

Impact of Membrane Drug Transporters on Resistance to Small-Molecule Tyrosine Kinase Inhibitors.

Trends Pharmacol Sci. 2016 Sep 19;

Authors: Neul C, Schaeffeler E, Sparreboom A, Laufer S, Schwab M, Nies AT

Abstract
Small-molecule inhibitors of tyrosine kinases (TKIs) are the mainstay of treatment for many malignancies and represent novel treatment options for other diseases such as idiopathic pulmonary fibrosis. Twenty-five TKIs are currently FDA-approved and >130 are being evaluated in clinical trials. Increasing evidence suggests that drug exposure of TKIs may significantly contribute to drug resistance, independently from somatic variation of TKI target genes. Membrane transport proteins may limit the amount of TKI reaching the target cells. This review highlights current knowledge on the basic and clinical pharmacology of membrane transporters involved in TKI disposition and their contribution to drug efficacy and adverse drug effects. In addition to non-genetic and epigenetic factors, genetic variants, particularly rare ones, in transporter genes are promising novel factors to explain interindividual variability in the response to TKI therapy.

PMID: 27659854 [PubMed - as supplied by publisher]

Response to "personalized medicine, genomics, and pharmacogenomics".

Clin J Oncol Nurs. 2014 Dec;18(6):618

Authors: Mayer DK

PMID: 25427694 [PubMed - indexed for MEDLINE]

Compact and highly active next-generation libraries for CRISPR-mediated gene repression and activation.

Elife. 2016 Sep 23;5

Authors: Horlbeck MA, Gilbert LA, Villalta JE, Adamson B, Pak RA, Chen Y, Fields AP, Park CY, Corn JE, Kampmann M, Weissman JS

Abstract
We recently found that nucleosomes directly block access of CRISPR/Cas9 to DNA (Horlbeck et al., 2016). Here, we build on this observation with a comprehensive algorithm that incorporates chromatin, position, and sequence features to accurately predict highly effective single guide RNAs (sgRNAs) for targeting nuclease-dead Cas9-mediated transcriptional repression (CRISPRi) and activation (CRISPRa). We use this algorithm to design next-generation genome-scale CRISPRi and CRISPRa libraries targeting human and mouse genomes. A CRISPRi screen for essential genes in K562 cells demonstrates that the large majority of sgRNAs are highly active. We also find CRISPRi does not exhibit any detectable non-specific toxicity recently observed with CRISPR nuclease approaches. Precision-recall analysis shows that we detect over 90% of essential genes with minimal false positives using a compact 5 sgRNA/gene library. Our results establish CRISPRi and CRISPRa as premier tools for loss- or gain-of-function studies and provide a general strategy for identifying Cas9 target sites.

PMID: 27661255 [PubMed - as supplied by publisher]

The global effect of exposing bakers' yeast to 5-fluoruracil and nystatin; a view to Toxichip.

Chemosphere. 2016 Feb;145:470-9

Authors: Graziano S, Gullì M, Maestri E, Marmiroli N

Abstract
A genome-wide screen of a haploid deletion library of bakers' yeast (Saccharomyces cerevisiae) was conducted to document the phenotypic and transcriptional impact of exposure to each of the two pharmaceutical products 5-fluorouracil (an anti-tumor agent) and nystatin (an anti-fungal agent). The combined data set was handled by applying a systems biology perspective. A Gene Ontology analysis identified functional categories previously characterized as likely targets for both compounds. Induced transcription profiles were well correlated in yeast and human HepG2 cells. The identified molecular targets for both compounds were used to suggest a small set of human orthologues as appropriate for testing on human material. The yeast system developed here (denoted "Toxichip") has likely utility for identifying biomarkers relevant for health and environmental risk assessment applications required as part of the development process for novel pharmaceuticals.

PMID: 26694798 [PubMed - indexed for MEDLINE]

Promise and Pragmatism in Clinical Microbiome Research.

Mini Rev Med Chem. 2015;16(3):222-4

Authors: Ajami NJ, Hutchinson DS, Petrosino JF

Abstract
The evolution of human microbiome research has lead to a systems biology approach that encompasses multidisciplinary investigations. The implementation of next generation sequencing technologies has allowed researchers to study unculturable organisms, discover novel ones, and provide insights into the role of the human microbiome in health and disease. When these approaches are applied to large-scale longitudinal studies designed to interrogate the association of the microbiome with specific clinical outcomes, the development of new therapeutics and diagnostics intended to modulate or detect changes in microbiome composition to improve human health are born. We are just starting to unravel the role of the microbiome in a wide-variety of diseases, and while some of it appears to be related to causation and provide opportunities for intervention, a good dose of pragmatism is warranted as the field is still in its infancy.

PMID: 26202196 [PubMed - indexed for MEDLINE]

Systems Biology and Biomarkers of Early Effects for Occupational Exposure Limit Setting.

J Occup Environ Hyg. 2015;12 Suppl 1:S41-54

Authors: DeBord DG, Burgoon L, Edwards SW, Haber LT, Kanitz MH, Kuempel E, Thomas RS, Yucesoy B

Abstract
In a recent National Research Council document, new strategies for risk assessment were described to enable more accurate and quicker assessments. This report suggested that evaluating individual responses through increased use of bio-monitoring could improve dose-response estimations. Identification of specific biomarkers may be useful for diagnostics or risk prediction as they have the potential to improve exposure assessments. This paper discusses systems biology, biomarkers of effect, and computational toxicology approaches and their relevance to the occupational exposure limit setting process. The systems biology approach evaluates the integration of biological processes and how disruption of these processes by chemicals or other hazards affects disease outcomes. This type of approach could provide information used in delineating the mode of action of the response or toxicity, and may be useful to define the low adverse and no adverse effect levels. Biomarkers of effect are changes measured in biological systems and are considered to be preclinical in nature. Advances in computational methods and experimental -omics methods that allow the simultaneous measurement of families of macromolecules such as DNA, RNA, and proteins in a single analysis have made these systems approaches feasible for broad application. The utility of the information for risk assessments from -omics approaches has shown promise and can provide information on mode of action and dose-response relationships. As these techniques evolve, estimation of internal dose and response biomarkers will be a critical test of these new technologies for application in risk assessment strategies. While proof of concept studies have been conducted that provide evidence of their value, challenges with standardization and harmonization still need to be overcome before these methods are used routinely.

PMID: 26132979 [PubMed - indexed for MEDLINE]

25 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

("orphan disease" OR "rare disease" OR "orphan diseases" OR "rare diseases")

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"Cystic Fibrosis"

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13 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

"Systems Biology"[Title/Abstract] AND ("2005/01/01"[PDAT] : "3000"[PDAT])

These pubmed results were generated on 2016/09/23

PubMed comprises more than 24 million citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

Impact of Predicting Health Care Utilization Via Web Search Behavior: A Data-Driven Analysis.

J Med Internet Res. 2016;18(9):e251

Authors: Agarwal V, Zhang L, Zhu J, Fang S, Cheng T, Hong C, Shah NH

Abstract
BACKGROUND: By recent estimates, the steady rise in health care costs has deprived more than 45 million Americans of health care services and has encouraged health care providers to better understand the key drivers of health care utilization from a population health management perspective. Prior studies suggest the feasibility of mining population-level patterns of health care resource utilization from observational analysis of Internet search logs; however, the utility of the endeavor to the various stakeholders in a health ecosystem remains unclear.
OBJECTIVE: The aim was to carry out a closed-loop evaluation of the utility of health care use predictions using the conversion rates of advertisements that were displayed to the predicted future utilizers as a surrogate. The statistical models to predict the probability of user's future visit to a medical facility were built using effective predictors of health care resource utilization, extracted from a deidentified dataset of geotagged mobile Internet search logs representing searches made by users of the Baidu search engine between March 2015 and May 2015.
METHODS: We inferred presence within the geofence of a medical facility from location and duration information from users' search logs and putatively assigned medical facility visit labels to qualifying search logs. We constructed a matrix of general, semantic, and location-based features from search logs of users that had 42 or more search days preceding a medical facility visit as well as from search logs of users that had no medical visits and trained statistical learners for predicting future medical visits. We then carried out a closed-loop evaluation of the utility of health care use predictions using the show conversion rates of advertisements displayed to the predicted future utilizers. In the context of behaviorally targeted advertising, wherein health care providers are interested in minimizing their cost per conversion, the association between show conversion rate and predicted utilization score, served as a surrogate measure of the model's utility.
RESULTS: We obtained the highest area under the curve (0.796) in medical visit prediction with our random forests model and daywise features. Ablating feature categories one at a time showed that the model performance worsened the most when location features were dropped. An online evaluation in which advertisements were served to users who had a high predicted probability of a future medical visit showed a 3.96% increase in the show conversion rate.
CONCLUSIONS: Results from our experiments done in a research setting suggest that it is possible to accurately predict future patient visits from geotagged mobile search logs. Results from the offline and online experiments on the utility of health utilization predictions suggest that such prediction can have utility for health care providers.

PMID: 27655225 [PubMed - as supplied by publisher]

Multidisciplinary model to implement pharmacogenomics at the point of care.

Genet Med. 2016 Sep 22;

Authors: Caraballo PJ, Hodge LS, Bielinski SJ, Stewart AK, Farrugia G, Schultz CG, Rohrer-Vitek CR, Olson JE, St Sauver JL, Roger VL, Parkulo MA, Kullo IJ, Nicholson WT, Elliott MA, Black JL, Weinshilboum RM

Abstract
PURPOSE: Despite potential clinical benefits, implementation of pharmacogenomics (PGx) faces many technical and clinical challenges. These challenges can be overcome with a comprehensive and systematic implementation model.
METHODS: The development and implementation of PGx were organized into eight interdependent components addressing resources, governance, clinical practice, education, testing, knowledge translation, clinical decision support (CDS), and maintenance. Several aspects of implementation were assessed, including adherence to the model, production of PGx-CDS interventions, and access to educational resources.
RESULTS: Between August 2012 and June 2015, 21 specific drug-gene interactions were reviewed and 18 of them were implemented in the electronic medical record as PGx-CDS interventions. There was complete adherence to the model with variable production time (98-392 days) and delay time (0-148 days). The implementation impacted approximately 1,247 unique providers and 3,788 unique patients. A total of 11 educational resources complementary to the drug-gene interactions and 5 modules specific for pharmacists were developed and implemented.
CONCLUSION: A comprehensive operational model can support PGx implementation in routine prescribing. Institutions can use this model as a roadmap to support similar efforts. However, we also identified challenges that will require major multidisciplinary and multi-institutional efforts to make PGx a universal reality.Genet Med advance online publication 22 September 2016Genetics in Medicine (2016); doi:10.1038/gim.2016.120.

PMID: 27657685 [PubMed - as supplied by publisher]

Impact of efavirenz pharmacokinetics and pharmacogenomics on neuropsychological performance in older HIV-infected patients.

J Antimicrob Chemother. 2016 Sep 21;

Authors: Sandkovsky U, Podany AT, Fletcher CV, Owen A, Felton-Coleman A, Winchester LC, Robertson K, Swindells S

Abstract
BACKGROUND: Pharmacokinetics (PK) and pharmacodynamics of efavirenz and its 8-hydroxy metabolite (8-OH-efavirenz) have not been robustly evaluated in older HIV-infected persons.
OBJECTIVES: We investigated relationships between neuropsychological (NP) performance and efavirenz and 8-OH-efavirenz PK in HIV-infected individuals >50 years of age.
METHODS: A cross-sectional study of HIV-infected adults on an efavirenz-containing regimen. The 12 and 18 h post-dose plasma efavirenz and 8-OH-efavirenz were quantified. CYP2B6 polymorphisms were investigated. Participants underwent neuropsychological tests; surveys were used for depression, sleep quality and anxiety. We investigated potential correlations of efavirenz and 8-OH-efavirenz plasma concentrations with NP performance, sleep, depression, anxiety and CYP2B6 polymorphisms.
RESULTS: Thirty participants (24 men and 6 women) with mean age 57 years (range 50-68). Plasma efavirenz concentrations did not correlate with NP performance; however, higher plasma 8-OH-efavirenz correlated with better learning (P = 0.002), language (P = 0.002) and total NP z-scores (P = 0.003). No correlation was seen for efavirenz or 8-OH-efavirenz with sleep, anxiety or depression. Median 12 and 18 h efavirenz plasma concentrations were 1967 ng/mL (IQR 1476-2394) and 1676 ng/mL (IQR 1120-2062), respectively. Median 12 and 18 h 8-OH-efavirenz plasma concentrations were 378 ng/mL (IQR 223-589) and 384 ng/mL (IQR 216-621), respectively. CYP2B6 G516T was associated with significantly higher plasma efavirenz at 12 and 18 h (P = 0.02) but not worse NP function.
CONCLUSIONS: Better neurocognitive functioning was associated with higher 8-OH-efavirenz but not efavirenz plasma concentrations. No correlation was observed with sleep or depression. These findings point to a need for greater understanding of the metabolic profile of efavirenz and 8-OH-efavirenz in plasma and the CNS and relationships with antiviral effect and neurotoxicity.

PMID: 27655857 [PubMed - as supplied by publisher]

Getting Pharmacogenomics Into the Clinic.

JAMA. 2016 Sep 21;

Authors: Abbasi J

PMID: 27653422 [PubMed - as supplied by publisher]

The role of pharmacogenetics and advances in gene therapy in the treatment of diabetic retinopathy.

Pharmacogenomics. 2016 Feb;17(3):309-20

Authors: Agarwal A, Ingham SA, Harkins KA, Do DV, Nguyen QD

Abstract
Diabetic retinopathy (DR) and its complications such as diabetic macular edema continue to remain a major cause for legal blindness in the developed world. While the introduction of anti-tVEGF agents has significantly improved visual outcomes of patients with DR, unpredictable response, largely due to genetic polymorphisms, appears to be a challenge with this therapy. With advances in identification of various genetic biomarkers, novel therapeutic strategies consisting of gene transfer are being developed and tested for patients with DR. Application of pharmacogenetic principles appears to be a promising futuristic strategy to attenuate diabetes-mediated retinal vasculopathy. In this comprehensive review, data from recent studies in the field of pharmacogenomics for the treatment of DR have been provided.

PMID: 26807609 [PubMed - indexed for MEDLINE]

Predictive or not predictive: understanding the mixed messages from the patient's DNA sequence.

J Clin Nurs. 2015 Dec;24(23-24):3730-5

Authors: Janssens AC, Patch C, Skirton H

Abstract
AIMS AND OBJECTIVES: The aim of this discussion paper is to enable nurses to understand how deoxyribonucleic acid analysis can be predictive for some diseases and not predictive for others. This will facilitate nurses to interpret genomic test results and explain them to patients.
BACKGROUND: Advances in technology mean that genetic testing is now commonly performed by sequencing the majority of an individual's genome or exome. This results in a huge amount of data, some of which can be used to predict or diagnose disease.
DESIGN: This is a discussion paper.
METHODS: This paper emerged from multiple discussions between the three authors over many months, culminating in a writing workshop to prepare this text.
RESULTS: The results of DNA analysis can be used to diagnose or predict rare diseases that are caused by a mutation in a single gene. However, while there are a number of genetic factors that contribute to common diseases, the ability to predict whether an individual will develop that condition is limited by the overall heritability of the condition. Environmental factors (such as lifestyle) are likely to be more useful in predicting common disease than genomic testing. Genomic tests may be of use to inform management of diseases in specific situations.
CONCLUSIONS: Genomic testing will be of use in diagnosing disorders due to single gene mutations, but the use of genomic testing to predict the chance of a patient being affected in the future by a common disease is unlikely to be a realistic option within a health service setting.
RELEVANCE TO CLINICAL PRACTICE: Nurses will increasingly be involved in the use of genomic tests in mainstream patient care. However, they need to understand and be able to explain to patients the practical applications of and limitations of such tests.

PMID: 26542756 [PubMed - indexed for MEDLINE]

Molecular mechanisms of rosmarinic acid from Salvia miltiorrhiza in acute lymphoblastic leukemia cells.

J Ethnopharmacol. 2015 Dec 24;176:55-68

Authors: Wu CF, Hong C, Klauck SM, Lin YL, Efferth T

Abstract
ETHNOPHARMACOLOGICAL RELEVANCE: Rosmarinic acid (RA), a major hydrosoluble bioactive compound found in the Chinese medicinal herb, Salvia miltiorrhiza Bunge, which has been used in traditional Chinese medicine to treat various diseases, including cancer. However, the mechanisms have not been fully elucidated.
AIM OF THE STUDY: Guided by microarray hybridization and Ingenuity Pathway Analysis, we identified modes of action of rosmarinic acid (RA) isolated from S. miltiorrhiza on acute lymphoblastic leukemia cells.
MATERIALS AND METHODS: Microarray data were verified by independent methods: Real-time RT-PCR (mRNA expression), resazurin assay (cytotoxicity of RA towards parental CCRF-CEM, multidrug-resistant CEM/ADR5000 cells and normal lymphocytes), flow cytometry (cell cycle arrest, apoptosis, necroptosis, generation of reactive oxygen species (ROS), disruption of mitochondrial membrane potential (MMP)), single cell gel electrophoresis (DNA damage), molecular docking and gene promoter binding motif analysis (NFκB), Western blotting (nuclear NFκB translocation, PARP cleavage, caspase 3/7/9 expression), and fibronectin-based cell adhesion assay.
RESULTS: RA dose-dependently inhibited CCRF-CEM and CEM/ADR5000 cells, but caused less cytotoxicity towards normal lymphocytes. RA simultaneously induced apoptosis and necrosis, as shown by cell morphology and annexin V-PI assay. DNA damage was dose-dependently induced without ROS generation, which subsequently led to cell cycle arrest. RA-stimulated MMP dysfunction activated PARP-cleavage and caspase-independent apoptosis. In accordance with molecular docking and gene promoter binding motif analyses, p65 translocation from the cytosol to the nucleus was blocked by RA, indicating a mechanistic role of the NFκB pathway to explain RA's action. RA affected cellular movement as evaluated by ameliorating cell adhesion to fibronectin.
CONCLUSIONS: RA induced apoptosis and necrosis in a ROS-independent DNA damage and caspase-independent manner. These results may contribute to the rationale use of S. miltiorrhiza and RA in traditional medicine of leukemia.

PMID: 26476154 [PubMed - indexed for MEDLINE]

Identifying the Uncertainty in Physician Practice Location through Spatial Analytics and Text Mining.

Int J Environ Res Public Health. 2016;13(9)

Authors: Shi X, Xue B, Xierali IM

Abstract
In response to the widespread concern about the adequacy, distribution, and disparity of access to a health care workforce, the correct identification of physicians' practice locations is critical to access public health services. In prior literature, little effort has been made to detect and resolve the uncertainty about whether the address provided by a physician in the survey is a practice address or a home address. This paper introduces how to identify the uncertainty in a physician's practice location through spatial analytics, text mining, and visual examination. While land use and zoning code, embedded within the parcel datasets, help to differentiate resident areas from other types, spatial analytics may have certain limitations in matching and comparing physician and parcel datasets with different uncertainty issues, which may lead to unforeseen results. Handling and matching the string components between physicians' addresses and the addresses of the parcels could identify the spatial uncertainty and instability to derive a more reasonable relationship between different datasets. Visual analytics and examination further help to clarify the undetectable patterns. This research will have a broader impact over federal and state initiatives and policies to address both insufficiency and maldistribution of a health care workforce to improve the accessibility to public health services.

PMID: 27657100 [PubMed - as supplied by publisher]

Extracting kinetic information from literature with KineticRE.

J Integr Bioinform. 2015;12(4):282

Authors: Freitas AA, Costa H, Rocha M, Rocha I

Abstract
To better understand the dynamic behavior of metabolic networks in a wide variety of conditions, the field of Systems Biology has increased its interest in the use of kinetic models. The different databases, available these days, do not contain enough data regarding this topic. Given that a significant part of the relevant information for the development of such models is still wide spread in the literature, it becomes essential to develop specific and powerful text mining tools to collect these data. In this context, this work has as main objective the development of a text mining tool to extract, from scientific literature, kinetic parameters, their respective values and their relations with enzymes and metabolites. The approach proposed integrates the development of a novel plug-in over the text mining framework @Note2. In the end, the pipeline developed was validated with a case study on Kluyveromyces lactis, spanning the analysis and results of 20 full text documents.

PMID: 26673933 [PubMed - indexed for MEDLINE]