Modeling and Re-Engineering of Azotobacter vinelandii Alginate Lyase to Enhance Its Catalytic Efficiency for Accelerating Biofilm Degradation.

PLoS One. 2016;11(6):e0156197

Authors: Jang CH, Piao YL, Huang X, Yoon EJ, Park SH, Lee K, Zhan CG, Cho H

Abstract
Alginate is known to prevent elimination of Pseudomonas aeruginosa biofilms. Alginate lyase (AlgL) might therefore facilitate treatment of Pseudomonas aeruginosa-infected cystic fibrosis patients. However, the catalytic activity of wild-type AlgL is not sufficiently high. Therefore, molecular modeling and site-directed mutagenesis of AlgL might assist in enzyme engineering for therapeutic development. AlgL, isolated from Azotobacter vinelandii, catalyzes depolymerization of alginate via a β-elimination reaction. AlgL was modeled based on the crystal structure template of Sphingomonas AlgL species A1-III. Based on this computational analysis, AlgL was subjected to site-directed mutagenesis to improve its catalytic activity. The kcat/Km of the K194E mutant showed a nearly 5-fold increase against the acetylated alginate substrate, as compared to the wild-type. Double and triple mutants (K194E/K245D, K245D/K319A, K194E/K245D/E312D, and K194E/K245D/K319A) were also prepared. The most potent mutant was observed to be K194E/K245D/K319A, which has a 10-fold improved kcat value (against acetylated alginate) compared to the wild-type enzyme. The antibiofilm effect of both AlgL forms was identified in combination with piperacillin/tazobactam (PT) and the disruption effect was significantly higher in mutant AlgL combined with PT than wild-type AlgL. However, for both the wild-type and K194E/K245D/K319A mutant, the use of the AlgL enzyme alone did not show significant antibiofilm effect.

PMID: 27253324 [PubMed - as supplied by publisher]

Lumacaftor/ivacaftor combination for cystic fibrosis patients homozygous for Phe508del-CFTR.

Drugs Today (Barc). 2016 Apr;52(4):229-37

Authors: Zhang W, Zhang X, Zhang YH, Strokes DC, Naren AP

Abstract
Cystic fibrosis (CF) is a life-shortening inherited disease caused by the loss or dysfunction of the CF transmembrane conductance regulator (CFTR) channel activity resulting from mutations in the CFTR gene. Phe508del is the most prevalent mutation, with approximately 90% of all CF patients carrying it on at least one allele. Over the past two or three decades, significant progress has been made in understanding the pathogenesis of CF, and in the development of effective CF therapies. The approval of Orkambi(R) (lumacaftor/ivacaftor) marks another milestone in CF therapeutics development, which, with the advent of personalized medicine, could potentially revolutionize CF care and management. This article reviews the rationale, progress and future direction in the development of lumacaftor/ivacaftor combination to treat CF patients.

PMID: 27252987 [PubMed - in process]

Heme Mobilization in Animals: A Metallolipid's Journey.

Acc Chem Res. 2016 Jun 2;

Authors: Reddi AR, Hamza I

Abstract
Heme is universally recognized as an essential and ubiquitous prosthetic group that enables proteins to carry out a diverse array of functions. All heme-dependent processes, from protein hemylation to heme signaling, require the dynamic and rapid mobilization of heme to hemoproteins present in virtually every subcellular compartment. The cytotoxicity and hydrophobicity of heme necessitates that heme mobilization is carefully controlled at the cellular and systemic level. However, the molecules and mechanisms that mediate heme homeostasis are poorly understood. In this Account, we provide a heuristic paradigm with which to conceptualize heme trafficking and highlight the most recent developments in the mechanisms underlying heme trafficking. As an iron-containing tetrapyrrole, heme exhibits properties of both transition metals and lipids. Accordingly, we propose its transport and trafficking will reflect principles gleaned from the trafficking of both metals and lipids. Using this conceptual framework, we follow the flow of heme from the final step of heme synthesis in the mitochondria to hemoproteins present in various subcellular organelles. Further, given that many cells and animals that cannot make heme can assimilate it intact from nutritional sources, we propose that intercellular heme trafficking pathways must exist. This necessitates that heme be able to be imported and exported from cells, escorted between cells and organs, and regulated at the organismal level via a coordinated systemic process. In this Account, we highlight recently discovered heme transport and trafficking factors and provide the biochemical foundation for the cell and systems biology of heme. Altogether, we seek to reconceptualize heme from an exchange inert cofactor buried in hemoprotein active sites to an exchange labile and mobile metallonutrient.

PMID: 27254265 [PubMed - as supplied by publisher]

Metabolomic Analysis in Brain Research: Opportunities and Challenges.

Front Physiol. 2016;7:183

Authors: Vasilopoulou CG, Margarity M, Klapa MI

Abstract
Metabolism being a fundamental part of molecular physiology, elucidating the structure and regulation of metabolic pathways is crucial for obtaining a comprehensive perspective of cellular function and understanding the underlying mechanisms of its dysfunction(s). Therefore, quantifying an accurate metabolic network activity map under various physiological conditions is among the major objectives of systems biology in the context of many biological applications. Especially for CNS, metabolic network activity analysis can substantially enhance our knowledge about the complex structure of the mammalian brain and the mechanisms of neurological disorders, leading to the design of effective therapeutic treatments. Metabolomics has emerged as the high-throughput quantitative analysis of the concentration profile of small molecular weight metabolites, which act as reactants and products in metabolic reactions and as regulatory molecules of proteins participating in many biological processes. Thus, the metabolic profile provides a metabolic activity fingerprint, through the simultaneous analysis of tens to hundreds of molecules of pathophysiological and pharmacological interest. The application of metabolomics is at its standardization phase in general, and the challenges for paving a standardized procedure are even more pronounced in brain studies. In this review, we support the value of metabolomics in brain research. Moreover, we demonstrate the challenges of designing and setting up a reliable brain metabolomic study, which, among other parameters, has to take into consideration the sex differentiation and the complexity of brain physiology manifested in its regional variation. We finally propose ways to overcome these challenges and design a study that produces reproducible and consistent results.

PMID: 27252656 [PubMed]

Impact of Pathogen Population Heterogeneity and Stress-Resistant Variants on Food Safety.

Annu Rev Food Sci Technol. 2016;7:439-56

Authors: Abee T, Koomen J, Metselaar KI, Zwietering MH, den Besten HM

Abstract
This review elucidates the state-of-the-art knowledge about pathogen population heterogeneity and describes the genotypic and phenotypic analyses of persister subpopulations and stress-resistant variants. The molecular mechanisms underlying the generation of persister phenotypes and genetic variants are identified. Zooming in on Listeria monocytogenes, a comparative whole-genome sequence analysis of wild types and variants that enabled the identification of mutations in variants obtained after a single exposure to lethal food-relevant stresses is described. Genotypic and phenotypic features are compared to those for persistent strains isolated from food processing environments. Inactivation kinetics, models used for fitting, and the concept of kinetic modeling-based schemes for detection of variants are presented. Furthermore, robustness and fitness parameters of L. monocytogenes wild type and variants are used to model their performance in food chains. Finally, the impact of stress-resistant variants and persistence in food processing environments on food safety is discussed.

PMID: 26772414 [PubMed - indexed for MEDLINE]

Advancing metabolic engineering through systems biology of industrial microorganisms.

Curr Opin Biotechnol. 2015 Dec;36:8-15

Authors: Dai Z, Nielsen J

Abstract
Development of sustainable processes to produce bio-based compounds is necessary due to the severe environmental problems caused by the use of fossil resources. Metabolic engineering can facilitate the development of highly efficient cell factories to produce these compounds from renewable resources. The objective of systems biology is to gain a comprehensive and quantitative understanding of living cells and can hereby enhance our ability to characterize and predict cellular behavior. Systems biology of industrial microorganisms is therefore valuable for metabolic engineering. Here we review the application of systems biology tools for the identification of metabolic engineering targets which may lead to reduced development time for efficient cell factories. Finally, we present some perspectives of systems biology for advancing metabolic engineering further.

PMID: 26318074 [PubMed - indexed for MEDLINE]

A Systems Biology Perspective on the Molecular Mechanisms Underlying the Therapeutic Effects of Buyang Huanwu Decoction on Ischemic Stroke.

Rejuvenation Res. 2015 Aug;18(4):313-25

Authors: Guo Q, Zhong M, Xu H, Mao X, Zhang Y, Lin N

Abstract
Ischemic stroke is the leading cause of adult disability worldwide. The outcome is worse in older patients, especially in terms of disability. Buyang Huanwu decoction (BHD), a famous traditional Chinese medicine formula, has been used extensively in the treatment of ischemic stroke for centuries. However, its pharmacological mechanisms have not been fully elucidated. In this study, 82 putative targets for 411 composite compounds contained in BHD were predicted on the basis of our previously developed target prediction system. On the basis of large-scale molecular docking, more than 80% compound-putative target pairs had medium to strong binding efficiency. The pharmacological networks of BHD were built according to relationships among herbs, putative targets, and known therapeutic targets for ischemic stroke, and 121 major nodes were identified by calculating three topological features-degree, node betweenness, and closeness. Importantly, the pathway enrichment analysis identified several signaling pathways involved with major putative targets of BHD, such as the calcium signaling pathway, vascular smooth muscle contraction, and nucleotide-binding oligomerization domain (NOD)-like receptor signaling pathway, which have not hitherto been reported. These data are expected to help find new therapeutic effects of BHD and optimize clinical use of this formula. Collectively, our study developed a comprehensive systems approach integrating drug target prediction and network and functional analyses to reveal the relationships of the herbs in BHD with their putative targets, and for the first time with ischemic stroke-related pathway systems. This is a pilot study based on bioinformatics analysis; thus, further experimental studies are required to validate our findings.

PMID: 25687091 [PubMed - indexed for MEDLINE]

Autism cornered: network analyses reveal mechanisms of autism spectrum disorders.

Mol Syst Biol. 2014;10:778

Authors: Auffray C

Abstract
Despite a wealth of behavioral, cognitive,biological, and genetic studies, the causes of autism have remained largely unknown.In their recent work, Snyder and colleagues(Li et al, 2014) use a systems biology approach and shed light on the molecular and cellular mechanisms underlying autism, thus opening novel avenues forunderstanding the disease and developing potential treatments.

PMID: 25549969 [PubMed - indexed for MEDLINE]

Systematic analysis of the molecular mechanism underlying atherosclerosis using a text mining approach.

Hum Genomics. 2016;10(1):14

Authors: Xi D, Zhao J, Lai W, Guo Z

Abstract
BACKGROUND: Atherosclerosis is one of the common health threats all over the world. It is a complex heritable disease that affects arterial blood vessels. Chronic inflammatory response plays an important role in atherogenesis. There has been little success in fully identifying functionally important genes in the pathogenesis of atherosclerosis.
RESULTS: In the present study, we performed a systematic analysis of atherosclerosis-related genes using text mining. We identified a total of 1312 genes. Gene ontology (GO) analysis revealed that a total of 35 terms exhibited significance (p < 0.05) as overrepresented terms, indicating that atherosclerosis invokes many genes with a wide range of different functions. Pathway analysis demonstrated that the most highly enriched pathway is the Toll-like receptor signaling pathway. Finally, through gene network analysis, we prioritized 48 genes using the hub gene method.
CONCLUSIONS: Our study provides a valuable resource for the in-depth understanding of the mechanism underlying atherosclerosis.

PMID: 27251057 [PubMed - in process]

19 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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8 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

"Cystic Fibrosis"

These pubmed results were generated on 2016/06/02

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11 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 2016/06/02

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.

The BioHub Knowledge Base: Ontology and Repository for Sustainable Biosourcing.

J Biomed Semantics. 2016;7(1):30

Authors: Read WJ, Demetriou G, Nenadic G, Ruddock N, Stevens R, Winter J

Abstract
BACKGROUND: The motivation for the BioHub project is to create an Integrated Knowledge Management System (IKMS) that will enable chemists to source ingredients from bio-renewables, rather than from non-sustainable sources such as fossil oil and its derivatives.
METHOD: The BioHubKB is the data repository of the IKMS; it employs Semantic Web technologies, especially OWL, to host data about chemical transformations, bio-renewable feedstocks, co-product streams and their chemical components. Access to this knowledge base is provided to other modules within the IKMS through a set of RESTful web services, driven by SPARQL queries to a Sesame back-end. The BioHubKB re-uses several bio-ontologies and bespoke extensions, primarily for chemical feedstocks and products, to form its knowledge organisation schema.
RESULTS: Parts of plants form feedstocks, while various processes generate co-product streams that contain certain chemicals. Both chemicals and transformations are associated with certain qualities, which the BioHubKB also attempts to capture. Of immediate commercial and industrial importance is to estimate the cost of particular sets of chemical transformations (leading to candidate surfactants) performed in sequence, and these costs too are captured. Data are sourced from companies' internal knowledge and document stores, and from the publicly available literature. Both text analytics and manual curation play their part in populating the ontology. We describe the prototype IKMS, the BioHubKB and the services that it supports for the IKMS.
AVAILABILITY: The BioHubKB can be found via http://biohub.cs.manchester.ac.uk/ontology/biohub-kb.owl .

PMID: 27246819 [PubMed - in process]

ODMedit: uniform semantic annotation for data integration in medicine based on a public metadata repository.

BMC Med Res Methodol. 2016;16(1):65

Authors: Dugas M, Meidt A, Neuhaus P, Storck M, Varghese J

Abstract
BACKGROUND: The volume and complexity of patient data - especially in personalised medicine - is steadily increasing, both regarding clinical data and genomic profiles: Typically more than 1,000 items (e.g., laboratory values, vital signs, diagnostic tests etc.) are collected per patient in clinical trials. In oncology hundreds of mutations can potentially be detected for each patient by genomic profiling. Therefore data integration from multiple sources constitutes a key challenge for medical research and healthcare.
METHODS: Semantic annotation of data elements can facilitate to identify matching data elements in different sources and thereby supports data integration. Millions of different annotations are required due to the semantic richness of patient data. These annotations should be uniform, i.e., two matching data elements shall contain the same annotations. However, large terminologies like SNOMED CT or UMLS don't provide uniform coding. It is proposed to develop semantic annotations of medical data elements based on a large-scale public metadata repository. To achieve uniform codes, semantic annotations shall be re-used if a matching data element is available in the metadata repository.
RESULTS: A web-based tool called ODMedit ( https://odmeditor.uni-muenster.de/ ) was developed to create data models with uniform semantic annotations. It contains ~800,000 terms with semantic annotations which were derived from ~5,800 models from the portal of medical data models (MDM). The tool was successfully applied to manually annotate 22 forms with 292 data items from CDISC and to update 1,495 data models of the MDM portal.
CONCLUSION: Uniform manual semantic annotation of data models is feasible in principle, but requires a large-scale collaborative effort due to the semantic richness of patient data. A web-based tool for these annotations is available, which is linked to a public metadata repository.

PMID: 27245222 [PubMed - in process]

Acceptability of a mobile health exercise-based cardiac rehabilitation intervention: a randomized trial.

J Cardiopulm Rehabil Prev. 2015 Sep-Oct;35(5):312-9

Authors: Pfaeffli Dale L, Whittaker R, Dixon R, Stewart R, Jiang Y, Carter K, Maddison R

Abstract
BACKGROUND: Mobile technologies (mHealth) have recently been used to deliver behavior change interventions; however, few have investigated the application of mHealth for treatment of ischemic heart disease (IHD). The Heart Exercise And Remote Technologies trial examined the effectiveness of an mHealth intervention to increase exercise behavior in adults with IHD. As a part of this trial, a process evaluation was conducted.
METHODS: One hundred seventy-one adults with IHD were randomized to receive a 6-month mHealth intervention (n = 85) plus usual care or usual care alone (n = 86). The intervention delivered a theory-based, automated package of exercise prescription and behavior change text messages and a supporting Web site. Three sources of data were triangulated to assess intervention participant perceptions: (1) Web site usage statistics; (2) feedback surveys; and (3) semistructured exit interviews. Descriptive information from survey and Web data were merged with qualitative data and analyzed using a semantic thematic approach.
RESULTS: At 24 weeks, all intervention participants provided Web usage statistics, 75 completed the feedback survey, and 17 were interviewed. Participants reported reading the text messages (70/75; 93%) and liked the content (55/75; 73%). The program motivated participants to exercise. Several suggestions to improve the program included further tailoring of the content (7/75; 7%) and increased personal contact (10/75; 13%).
CONCLUSIONS: Adults with IHD were able to use an mHealth program and reported that text messaging is a good way to deliver exercise information. While mHealth is designed to be automated, programs might be improved if content and delivery were tailored to individual needs.

PMID: 26181037 [PubMed - indexed for MEDLINE]

An ontology for Autism Spectrum Disorder (ASD) to infer ASD phenotypes from Autism Diagnostic Interview-Revised data.

J Biomed Inform. 2015 Aug;56:333-47

Authors: Mugzach O, Peleg M, Bagley SC, Guter SJ, Cook EH, Altman RB

Abstract
OBJECTIVE: Our goal is to create an ontology that will allow data integration and reasoning with subject data to classify subjects, and based on this classification, to infer new knowledge on Autism Spectrum Disorder (ASD) and related neurodevelopmental disorders (NDD). We take a first step toward this goal by extending an existing autism ontology to allow automatic inference of ASD phenotypes and Diagnostic & Statistical Manual of Mental Disorders (DSM) criteria based on subjects' Autism Diagnostic Interview-Revised (ADI-R) assessment data.
MATERIALS AND METHODS: Knowledge regarding diagnostic instruments, ASD phenotypes and risk factors was added to augment an existing autism ontology via Ontology Web Language class definitions and semantic web rules. We developed a custom Protégé plugin for enumerating combinatorial OWL axioms to support the many-to-many relations of ADI-R items to diagnostic categories in the DSM. We utilized a reasoner to infer whether 2642 subjects, whose data was obtained from the Simons Foundation Autism Research Initiative, meet DSM-IV-TR (DSM-IV) and DSM-5 diagnostic criteria based on their ADI-R data.
RESULTS: We extended the ontology by adding 443 classes and 632 rules that represent phenotypes, along with their synonyms, environmental risk factors, and frequency of comorbidities. Applying the rules on the data set showed that the method produced accurate results: the true positive and true negative rates for inferring autistic disorder diagnosis according to DSM-IV criteria were 1 and 0.065, respectively; the true positive rate for inferring ASD based on DSM-5 criteria was 0.94.
DISCUSSION: The ontology allows automatic inference of subjects' disease phenotypes and diagnosis with high accuracy.
CONCLUSION: The ontology may benefit future studies by serving as a knowledge base for ASD. In addition, by adding knowledge of related NDDs, commonalities and differences in manifestations and risk factors could be automatically inferred, contributing to the understanding of ASD pathophysiology.

PMID: 26151311 [PubMed - indexed for MEDLINE]

Comparing image search behaviour in the ARRS GoldMiner search engine and a clinical PACS/RIS.

J Biomed Inform. 2015 Aug;56:57-64

Authors: De-Arteaga M, Eggel I, Do B, Rubin D, Kahn CE, Müller H

Abstract
Information search has changed the way we manage knowledge and the ubiquity of information access has made search a frequent activity, whether via Internet search engines or increasingly via mobile devices. Medical information search is in this respect no different and much research has been devoted to analyzing the way in which physicians aim to access information. Medical image search is a much smaller domain but has gained much attention as it has different characteristics than search for text documents. While web search log files have been analysed many times to better understand user behaviour, the log files of hospital internal systems for search in a PACS/RIS (Picture Archival and Communication System, Radiology Information System) have rarely been analysed. Such a comparison between a hospital PACS/RIS search and a web system for searching images of the biomedical literature is the goal of this paper. Objectives are to identify similarities and differences in search behaviour of the two systems, which could then be used to optimize existing systems and build new search engines. Log files of the ARRS GoldMiner medical image search engine (freely accessible on the Internet) containing 222,005 queries, and log files of Stanford's internal PACS/RIS search called radTF containing 18,068 queries were analysed. Each query was preprocessed and all query terms were mapped to the RadLex (Radiology Lexicon) terminology, a comprehensive lexicon of radiology terms created and maintained by the Radiological Society of North America, so the semantic content in the queries and the links between terms could be analysed, and synonyms for the same concept could be detected. RadLex was mainly created for the use in radiology reports, to aid structured reporting and the preparation of educational material (Lanlotz, 2006) [1]. In standard medical vocabularies such as MeSH (Medical Subject Headings) and UMLS (Unified Medical Language System) specific terms of radiology are often underrepresented, therefore RadLex was considered to be the best option for this task. The results show a surprising similarity between the usage behaviour in the two systems, but several subtle differences can also be noted. The average number of terms per query is 2.21 for GoldMiner and 2.07 for radTF, the used axes of RadLex (anatomy, pathology, findings, …) have almost the same distribution with clinical findings being the most frequent and the anatomical entity the second; also, combinations of RadLex axes are extremely similar between the two systems. Differences include a longer length of the sessions in radTF than in GoldMiner (3.4 and 1.9 queries per session on average). Several frequent search terms overlap but some strong differences exist in the details. In radTF the term "normal" is frequent, whereas in GoldMiner it is not. This makes intuitive sense, as in the literature normal cases are rarely described whereas in clinical work the comparison with normal cases is often a first step. The general similarity in many points is likely due to the fact that users of the two systems are influenced by their daily behaviour in using standard web search engines and follow this behaviour in their professional search. This means that many results and insights gained from standard web search can likely be transferred to more specialized search systems. Still, specialized log files can be used to find out more on reformulations and detailed strategies of users to find the right content.

PMID: 26002820 [PubMed - indexed for MEDLINE]

Pharmacogenomics, Pharmacokinetics, and Pharmacodynamics in the Era of Targeted Therapies.

Am Soc Clin Oncol Educ Book. 2016;35:e175-e184

Authors: Calvo E, Walko C, Dees EC, Valenzuela B

Abstract
The complex nature of the pharmacologic aspects of cancer therapeutics has become more apparent in the past several years with the arrival of a cascade of target-based agents and the difficult challenge of bringing individualized precision medicine to oncology. Interpatient variability in drug action, singularly in novel agents, is in part caused by pharmacogenomic (PG), pharmacokinetic, and pharmacodynamic (PD) factors, and drug selection and dosing should take this into consideration to optimize the benefit for our patients in terms of antitumor activity and treatment tolerance. In this regard, somatic genetic evaluation of tumors is useful in not only predicting response to initial targeted therapies but also in anticipating and guiding therapy after the development of acquired resistance; therapeutic drug monitoring of novel small molecules and monoclonal antibodies must be incorporated in our day-to-day practice to minimize the negative effect on clinical outcome of interindividual variability on pharmacokinetic processes of these drugs for all patients, but especially for fragile patient populations and those with organ dysfunction or comorbidities. For these populations, incorporating frailty assessment tools into trials of newer agents and validating frailty-based dose adjustment should be an important part of further drug development.

PMID: 27249721 [PubMed - as supplied by publisher]

Evidence for extensive pleiotropy among pharmacogenes.

Pharmacogenomics. 2016 Jun 1;:0

Authors: Oetjens MT, Bush WS, Denny JC, Birdwell K, Kodaman N, Verma A, Dilks HH, Pendergrass SA, Ritchie MD, Crawford DC

Abstract
AIM: We sought to identify potential pleiotropy involving pharmacogenes.
METHODS: We tested 184 functional variants in 34 pharmacogenes for associations using a custom grouping of International Classification and Disease, Ninth Revision billing codes extracted from deidentified electronic health records of 6892 patients.
RESULTS: We replicated several associations including ABCG2 (rs2231142) and gout (p = 1.73 × 10(-7); odds ratio [OR]: 1.73; 95% CI: 1.40-2.12); and SLCO1B1 (rs4149056) and jaundice (p = 2.50 × 10(-4); OR: 1.67; 95% CI: 1.27-2.20).
CONCLUSION: In this systematic screen for phenotypic associations with functional variants, several novel genotype-phenotype combinations also achieved phenome-wide significance, including SLC15A2 rs1143672 and renal osteodystrophy (p = 2.67 × 10(-) (6); OR: 0.61; 95% CI: 0.49-0.75).

PMID: 27249515 [PubMed - as supplied by publisher]

Requirements for comprehensive pharmacogenetic genotyping platforms.

Pharmacogenomics. 2016 Jun 1;:0

Authors: Lauschke VM, Ingelman-Sundberg M

Abstract
Recent research highlighted the large extent of rare variants in pharmacogenes and, on this basis, it was estimated that rare variants account for 30-40% of the functional variability in pharmacogenes. It has been proposed that comprehensive next-generation sequencing (NGS)-based sequencing of pharmacogenes could soon be a cost-effective methodology for clinical routine genotyping. Yet, multiple challenges on technical, interpretative and ethical levels need to be overcome to enable the reasonable dissemination of comprehensive pharmacogenetic genotyping, that includes rare genetic variation, into clinical practice. We argue that current pre-emptive pharmacogenetic testing cannot be based on comprehensive approaches but needs to be restricted to validated variants. Rather, comprehensive strategies should only be used for retrospective analyses of patients exhibiting unanticipated drug responses. Thereby, subsequent to computational analyses and functional validations, emerging variants with confirmed functional relevance can be incorporated into candidate genotyping strategies, thus refining and enhancing future pre-emptive genetic testing.

PMID: 27248710 [PubMed - as supplied by publisher]