The International SSRI Pharmacogenomics Consortium (ISPC): a genome-wide association study of antidepressant treatment response.

Transl Psychiatry. 2016 Nov 1;6(11):e937

Authors: Biernacka JM, Sangkuhl K, Jenkins G, Whaley RM, Barman P, Batzler A, Altman RB, Arolt V, Brockmöller J, Chen CH, Domschke K, Hall-Flavin DK, Hong CJ, Illi A, Ji Y, Kampman O, Kinoshita T, Leinonen E, Liou YJ, Mushiroda T, Nonen S, Skime MK, Wang L, Baune BT, Kato M, Liu YL, Praphanphoj V, Stingl JC, Tsai SJ, Kubo M, Klein TE, Weinshilboum R

PMID: 27801898 [PubMed - in process]

Positional proteomics in the era of the human proteome project on the doorstep of precision medicine.

Biochimie. 2016 Mar;122:110-8

Authors: Eckhard U, Marino G, Butler GS, Overall CM

Abstract
Proteolytic processing is a pervasive and irreversible post-translational modification that expands the protein universe by generating new proteoforms (protein isoforms). Unlike signal peptide or prodomain removal, protease-generated proteoforms can rarely be predicted from gene sequences. Positional proteomic techniques that enrich for N- or C-terminal peptides from proteomes are indispensable for a comprehensive understanding of a protein's function in biological environments since protease cleavage frequently results in altered protein activity and localization. Proteases often process other proteases and protease inhibitors which perturbs proteolytic networks and potentiates the initial cleavage event to affect other molecular networks and cellular processes in physiological and pathological conditions. This review is aimed at researchers with a keen interest in state of the art systems level positional proteomic approaches that: (i) enable the study of complex protease-protease, protease-inhibitor and protease-substrate crosstalk and networks; (ii) allow the identification of proteolytic signatures as candidate disease biomarkers; and (iii) are expected to fill the Human Proteome Project missing proteins gap. We predict that these methodologies will be an integral part of emerging precision medicine initiatives that aim to customize healthcare, converting reactive medicine into a personalized and proactive approach, improving clinical care and maximizing patient health and wellbeing, while decreasing health costs by eliminating ineffective therapies, trial-and-error prescribing, and adverse drug effects. Such initiatives require quantitative and functional proteome profiling and dynamic disease biomarkers in addition to current pharmacogenomics approaches. With proteases at the pathogenic center of many diseases, high-throughput protein termini identification techniques such as TAILS (Terminal Amine Isotopic Labeling of Substrates) and COFRADIC (COmbined FRActional DIagonal Chromatography) will be fundamental for individual and comprehensive assessment of health and disease.

PMID: 26542287 [PubMed - indexed for MEDLINE]

Intravenous immunoglobulin, pharmacogenomics, and Kawasaki disease.

J Microbiol Immunol Infect. 2016 Feb;49(1):1-7

Authors: Kuo HC, Hsu YW, Wu MS, Chien SC, Liu SF, Chang WC

Abstract
Kawasaki disease (KD) is a systemic vasculitis of unknown etiology and it is therefore worth examining the multifactorial interaction of genes and environmental factors. Targeted genetic association and genome-wide association studies have helped to provide a better understanding of KD from infection to the immune-related response. Findings in the past decade have contributed to a major breakthrough in the genetics of KD, with the identification of several genomic regions linked to the pathogenesis of KD, including ITPKC, CD40, BLK, and FCGR2A. This review focuses on the factors associated with the genetic polymorphisms of KD and the pharmacogenomics of the response to treatment in patients with intravenous immunoglobulin resistance.

PMID: 25556045 [PubMed - indexed for MEDLINE]

OGEE v2: an update of the online gene essentiality database with special focus on differentially essential genes in human cancer cell lines.

Nucleic Acids Res. 2016 Oct 30;:

Authors: Chen WH, Lu G, Chen X, Zhao XM, Bork P

Abstract
OGEE is an Online GEne Essentiality database. To enhance our understanding of the essentiality of genes, in OGEE we collected experimentally tested essential and non-essential genes, as well as associated gene properties known to contribute to gene essentiality. We focus on large-scale experiments, and complement our data with text-mining results. We organized tested genes into data sets according to their sources, and tagged those with variable essentiality statuses across data sets as conditionally essential genes, intending to highlight the complex interplay between gene functions and environments/experimental perturbations. Developments since the last public release include increased numbers of species and gene essentiality data sets, inclusion of non-coding essential sequences and genes with intermediate essentiality statuses. In addition, we included 16 essentiality data sets from cancer cell lines, corresponding to 9 human cancers; with OGEE, users can easily explore the shared and differentially essential genes within and between cancer types. These genes, especially those derived from cell lines that are similar to tumor samples, could reveal the oncogenic drivers, paralogous gene expression pattern and chromosomal structure of the corresponding cancer types, and can be further screened to identify targets for cancer therapy and/or new drug development. OGEE is freely available at http://ogee.medgenius.info.

PMID: 27799467 [PubMed - as supplied by publisher]

Identification of a RAI1-associated disease network through integration of exome sequencing, transcriptomics, and 3D genomics.

Genome Med. 2016 Nov 1;8(1):105

Authors: Loviglio MN, Beck CR, White JJ, Leleu M, Harel T, Guex N, Niknejad A, Bi W, Chen ES, Crespo I, Yan J, Charng WL, Gu S, Fang P, Coban-Akdemir Z, Shaw CA, Jhangiani SN, Muzny DM, Gibbs RA, Rougemont J, Xenarios I, Lupski JR, Reymond A

Abstract
BACKGROUND: Smith-Magenis syndrome (SMS) is a developmental disability/multiple congenital anomaly disorder resulting from haploinsufficiency of RAI1. It is characterized by distinctive facial features, brachydactyly, sleep disturbances, and stereotypic behaviors.
METHODS: We investigated a cohort of 15 individuals with a clinical suspicion of SMS who showed neither deletion in the SMS critical region nor damaging variants in RAI1 using whole exome sequencing. A combination of network analysis (co-expression and biomedical text mining), transcriptomics, and circularized chromatin conformation capture (4C-seq) was applied to verify whether modified genes are part of the same disease network as known SMS-causing genes.
RESULTS: Potentially deleterious variants were identified in nine of these individuals using whole-exome sequencing. Eight of these changes affect KMT2D, ZEB2, MAP2K2, GLDC, CASK, MECP2, KDM5C, and POGZ, known to be associated with Kabuki syndrome 1, Mowat-Wilson syndrome, cardiofaciocutaneous syndrome, glycine encephalopathy, mental retardation and microcephaly with pontine and cerebellar hypoplasia, X-linked mental retardation 13, X-linked mental retardation Claes-Jensen type, and White-Sutton syndrome, respectively. The ninth individual carries a de novo variant in JAKMIP1, a regulator of neuronal translation that was recently found deleted in a patient with autism spectrum disorder. Analyses of co-expression and biomedical text mining suggest that these pathologies and SMS are part of the same disease network. Further support for this hypothesis was obtained from transcriptome profiling that showed that the expression levels of both Zeb2 and Map2k2 are perturbed in Rai1 (-/-) mice. As an orthogonal approach to potentially contributory disease gene variants, we used chromatin conformation capture to reveal chromatin contacts between RAI1 and the loci flanking ZEB2 and GLDC, as well as between RAI1 and human orthologs of the genes that show perturbed expression in our Rai1 (-/-) mouse model.
CONCLUSIONS: These holistic studies of RAI1 and its interactions allow insights into SMS and other disorders associated with intellectual disability and behavioral abnormalities. Our findings support a pan-genomic approach to the molecular diagnosis of a distinctive disorder.

PMID: 27799067 [PubMed - in process]

15 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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16 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

"Cystic Fibrosis"

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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 2016/11/01

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.

Aripiprazole, an Antipsychotic and Partial Dopamine Agonist, Inhibits Cancer Stem Cells and Reverses Chemoresistance.

Anticancer Res. 2016 Oct;36(10):5153-5161

Authors: Suzuki S, Okada M, Kuramoto K, Takeda H, Sakaki H, Watarai H, Sanomachi T, Seino S, Yoshioka T, Kitanaka C

Abstract
BACKGROUND: There is a growing interest in repurposing antipsychotic dopamine antagonists for cancer treatment; however, antipsychotics are often associated with an increased risk of fatal events. The anticancer activities of aripiprazole, an antipsychotic drug with partial dopamine agonist activity and an excellent safety profile, remain unknown.
MATERIALS AND METHODS: The effects of aripiprazole alone or in combination with chemotherapeutic agents on the growth, sphere-forming ability and stem cell/differentiation/chemoresistance marker expression of cancer stem cells, serum-cultured cancer cells from which they were derived, and normal cells were examined.
RESULTS: At concentrations non-toxic to normal cells, aripiprazole inhibited the growth of serum-cultured cancer cells and cancer stem cells. Furthermore, aripiprazole induced differentiation and inhibited sphere formation, as well as stem cell marker expression of cancer stem cells while inhibiting their survivin expression and sensitizing them to chemotherapeutic agents.
CONCLUSION: Repurposing aripiprazole as an anticancer stem cell drug may merit further consideration.

PMID: 27798875 [PubMed - in process]

Current Progress in Bioinformatics 2016.

Brief Bioinform. 2016 Jan;17(1):1

Authors: Altman R

PMID: 26628559 [PubMed - indexed for MEDLINE]

Recent Advances and Emerging Applications in Text and Data Mining for Biomedical Discovery.

Brief Bioinform. 2016 Jan;17(1):33-42

Authors: Gonzalez GH, Tahsin T, Goodale BC, Greene AC, Greene CS

Abstract
Precision medicine will revolutionize the way we treat and prevent disease. A major barrier to the implementation of precision medicine that clinicians and translational scientists face is understanding the underlying mechanisms of disease. We are starting to address this challenge through automatic approaches for information extraction, representation and analysis. Recent advances in text and data mining have been applied to a broad spectrum of key biomedical questions in genomics, pharmacogenomics and other fields. We present an overview of the fundamental methods for text and data mining, as well as recent advances and emerging applications toward precision medicine.

PMID: 26420781 [PubMed - indexed for MEDLINE]

Repurposing some older drugs that cross the blood-brain barrier and have potential anticancer activity to provide new treatment options for glioblastoma.

Br J Clin Pharmacol. 2016 Feb;81(2):199-209

Authors: Rundle-Thiele D, Head R, Cosgrove L, Martin JH

Abstract
Glioblastoma is a brain neoplasm with limited 5-year survival rates. Developments of new treatment regimens that improve patient survival in patients with glioblastoma are needed. It is likely that a number of existing drugs used in other conditions have potential anticancer effects that offer significant survival benefit to glioblastoma patients. Identification of such drugs could provide a novel treatment paradigm.

PMID: 26374633 [PubMed - indexed for MEDLINE]

Metformin for Prevention and Treatment of Colon Cancer: A Reappraisal of Experimental and Clinical Data.

Curr Drug Targets. 2016;17(4):439-46

Authors: Anisimov VN

Abstract
In the 70-80th of last century, it has been shown that the antidiabetic biguanide drugs phenformin (PF) and buformin (BF) can exert an inhibitory action on carcinogenesis in animal models and increase from 5 to 10-years survival of cancer patients. Since 2005, after first evidence publication of the capacity of metformin (MF), another biguanide, to prevent development of malignant tumors in individuals with type 2 diabetes (T2D) and suppress tumorigenesis in mice, the burst of studies started in this field focused on breast, pancreas, prostatic, endometrial and some other cancers. Colorectal cancer (CRC) is the most prevalent among digestive system cancers. In this mini-review are presented the available data on the capacity of antidiabetic biguanide drugs to prevent colorectal carcinogenesis and growth in vitro and in vivo in experimental models and clinical observations.

PMID: 25738299 [PubMed - indexed for MEDLINE]

Isomorphic semantic mapping of variant call format (VCF2RDF).

Bioinformatics. 2016 Oct 25;:

Authors: Penha ED, Iriabho E, Dussaq A, Magalhães de Oliveira D, Almeida JS

Abstract
The move of computational genomics workflows to Cloud Computing platforms is associated with a new level of integration and interoperability that challenges existing data representation formats. The Variant Calling Format (VCF) is in a particularly sensitive position in that regard, with both clinical and consumer-facing analysis tools relying on this self-contained description of genomic variation in Next Generation Sequencing (NGS) results. In this report we identify an isomorphic map between VCF and the reference Resource Description Framework. RDF is advanced by the World Wide Web Consortium (W3C) to enable representations of linked data that are both distributed and discoverable. The resulting ability to decompose VCF reports of genomic variation without loss of context addresses the need to modularize and govern NGS pipelines for Precision Medicine. Specifically, it provides the flexibility (i.e. the indexing) needed to support the wide variety of clinical scenarios and patient-facing governance where only part of the VCF data is fitting.
IMPLEMENTATION: Software libraries with a claim to be both domain-facing and consumer-facing have to pass the test of portability across the variety of devices that those consumers in fact adopt. That is, ideally the implementation should itself take place within the space defined by web technologies. Consequently, the isomorphic mapping function was implemented in JavaScript, and was tested in a variety of environments and devices, client and server side alike. These range from web browsers in mobile phones to the most popular micro service platform, NodeJS.
AVAILABILITY: The code is publicly available at https://github.com/ibl/VCFr , with a live deployment at: http://ibl.github.io/VCFr/ CONTACT: Jonas.almeida@stonybrook.edu.

PMID: 27797761 [PubMed - as supplied by publisher]

Lessons learned in the generation of biomedical research datasets using Semantic Open Data technologies.

Stud Health Technol Inform. 2015;210:165-9

Authors: Legaz-García Mdel C, Miñarro-Giménez JA, Menárguez-Tortosa M, Fernández-Breis JT

Abstract
Biomedical research usually requires combining large volumes of data from multiple heterogeneous sources. Such heterogeneity makes difficult not only the generation of research-oriented dataset but also its exploitation. In recent years, the Open Data paradigm has proposed new ways for making data available in ways that sharing and integration are facilitated. Open Data approaches may pursue the generation of content readable only by humans and by both humans and machines, which are the ones of interest in our work. The Semantic Web provides a natural technological space for data integration and exploitation and offers a range of technologies for generating not only Open Datasets but also Linked Datasets, that is, open datasets linked to other open datasets. According to the Berners-Lee's classification, each open dataset can be given a rating between one and five stars attending to can be given to each dataset. In the last years, we have developed and applied our SWIT tool, which automates the generation of semantic datasets from heterogeneous data sources. SWIT produces four stars datasets, given that fifth one can be obtained by being the dataset linked from external ones. In this paper, we describe how we have applied the tool in two projects related to health care records and orthology data, as well as the major lessons learned from such efforts.

PMID: 25991123 [PubMed - indexed for MEDLINE]

Economic Evaluation of a Pharmacogenomics Test for Statin-Induced Myopathy in Cardiovascular High-Risk Patients Initiating a Statin.

Mol Diagn Ther. 2016 Oct 31;

Authors: Mitchell D, Guertin JR, Iliza AC, Fanton-Aita F, LeLorier J

Abstract
BACKGROUND: Statins are the mainstay hypercholesterolemia treatment and reduce the risk of cardiovascular events in patients. However, statin therapy is often interrupted in patients experiencing musculoskeletal pain or myopathy, which are common in this patient group. Currently, the standard tests for diagnosing statin myopathies are difficult to interpret. A pharmacogenomics (PGx) test to diagnose statin-induced myopathy would be highly desirable.
METHODS: We developed a Markov state model to assess the cost-effectiveness of a hypothetical PGx test, which aims to identify statin-induced myopathy in high-risk, secondary prevention cardiovascular patients. The alternative strategy hypothesized is that physicians or patients interrupt the statin therapy in the presence of musculoskeletal pain. Our model includes health states specific to the PGx test outcome which assesses the impact of test errors.
RESULTS: Assuming a perfect test, the results indicate that the PGx test strategy dominates when the test costs less than CAN$356, when the strategy is cost neutral. These results are robust to deterministic and probabilistic sensitivity analyses.
CONCLUSION: Our base-case results show that a PGx test for statin-induced myopathy in a high-risk, secondary prevention of a cardiovascular event population would be a dominant solution for a test cost of CAN$356 or less. Furthermore, the modelling of the complete range of diagnostic test outcomes provide a broader understanding of the economic value of the pharmacogenomics test.

PMID: 27798813 [PubMed - as supplied by publisher]

Genomic sequencing of uric acid metabolizing and clearing genes in relationship to xanthine oxidase inhibitor dose.

Rheumatol Int. 2016 Oct 31;

Authors: Carroll MB, Smith DM, Shaak TL

Abstract
It remains unclear why the dose of xanthine oxidase inhibitors (XOI) allopurinol or febuxostat varies among patients though they reach similar serum uric acid (SUA) goal. We pursued genomic sequencing of XOI metabolism and clearance genes to identify single-nucleotide polymorphisms (SNPs) relate to differences in XOI dose. Subjects with a diagnosis of Gout based on the 1977 American College of Rheumatology Classification Criteria for the disorder, who were on stable doses of a XOI, and who were at their goal SUA level, were enrolled. The primary outcome was relationship between SNPs in any of these genes to XOI dose. The secondary outcome was relationship between SNPs and change in pre- and post-treatment SUA. We enrolled 100 subjects. The average patient age was 68.6 ± 10.6 years old. Over 80% were men and 77% were Caucasian. One SNP was associated with a higher XOI dose: rs75995567 (p = 0.031). Two SNPs were associated with 300 mg daily of allopurinol: rs11678615 (p = 0.022) and rs3731722 on Aldehyde Oxidase (AO) (His1297Arg) (p = 0.001). Two SNPs were associated with a lower dose of allopurinol: rs1884725 (p = 0.033) and rs34650714 (p = 0.006). For the secondary outcome, rs13415401 was the only SNP related to a smaller mean SUA change. Ten SNPs were identified with a larger change in SUA. Though multiple SNPs were identified in the primary and secondary outcomes of this study, rs3731722 is known to alter catalytic function for some aldehyde oxidase substrates.

PMID: 27798726 [PubMed - as supplied by publisher]

Pharmacogenomic study using bio- and nanobioelectrochemistry: Drug-DNA interaction.

Mater Sci Eng C Mater Biol Appl. 2016 Apr 1;61:1002-17

Authors: Hasanzadeh M, Shadjou N

Abstract
Small molecules that bind genomic DNA have proven that they can be effective anticancer, antibiotic and antiviral therapeutic agents that affect the well-being of millions of people worldwide. Drug-DNA interaction affects DNA replication and division; causes strand breaks, and mutations. Therefore, the investigation of drug-DNA interaction is needed to understand the mechanism of drug action as well as in designing DNA-targeted drugs. On the other hand, the interaction between DNA and drugs can cause chemical and conformational modifications and, thus, variation of the electrochemical properties of nucleobases. For this purpose, electrochemical methods/biosensors can be used toward detection of drug-DNA interactions. The present paper reviews the drug-DNA interactions, their types and applications of electrochemical techniques used to study interactions between DNA and drugs or small ligand molecules that are potentially of pharmaceutical interest. The results are used to determine drug binding sites and sequence preference, as well as conformational changes due to drug-DNA interactions. Also, the intention of this review is to give an overview of the present state of the drug-DNA interaction cognition. The applications of electrochemical techniques for investigation of drug-DNA interaction were reviewed and we have discussed the type of qualitative or quantitative information that can be obtained from the use of each technique.

PMID: 26838928 [PubMed - indexed for MEDLINE]

Individualization of antiretroviral therapy--pharmacogenomic aspect.

Indian J Med Res. 2015 Dec;142(6):663-74

Authors: Dalal B, Shankarkumar A, Ghosh K

Abstract
Combination therapy with three drug regimens for human immunodeficiency virus (HIV) infection significantly suppresses the viral replication. However, this therapeutic impact is restricted by adverse drug events and response in terms of short and long term efficacy. There are multiple factors involved in different responses to antiretrovirals (ARVs) such as age, body weight, disease status, diet and heredity. Pharmacogenomics deals with individual genetic make-up and its role in drug efficacy and toxicity. In depth genetic research has provided evidence to predict the risk of developing certain toxicities for which personalized screening and surveillance protocols may be developed to prevent side effects. Here we describe the use of pharmacogenomics for optimal use of HAART (highly active antiretroviral therapy).

PMID: 26831415 [PubMed - indexed for MEDLINE]

Advances in the Pharmacogenomics of Adverse Drug Reactions.

Drug Saf. 2016 Jan;39(1):15-27

Authors: Collins SL, Carr DF, Pirmohamed M

Abstract
Rapid developments in pharmacogenomics have been noticeable in recent years, and much of this knowledge has improved understanding of adverse drug reactions. This improved knowledge has largely been the result of improved sequencing technologies and falling costs in this area, as well as improved statistical techniques to analyse the data derived from studies. While the genetic reasons behind adverse drug reactions are becoming better understood, translation of this knowledge, particularly in terms of biomarkers that might be clinically applicable at the bedside, has been more difficult. Understanding of the technologies and their application is limited among practising clinicians. The cost of some of the technologies available may also be prohibitive in stretched healthcare economies. As education about the potential for applying pharmacogenomics improves and costs fall, understanding of adverse drug reactions and application of this knowledge in a clinical setting should improve.

PMID: 26650062 [PubMed - indexed for MEDLINE]