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Georgitsi M, Patrinos GP. Genetic databases in pharmacogenomics: the Frequency of Inherited Disorders Database (FINDbase). Methods Mol Biol 2013; 1015:321-336. [PMID: 23824866 DOI: 10.1007/978-1-62703-435-7_21] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/02/2023]
Abstract
Pharmacogenomics studies how the variations of the individuals' genetic makeup are correlated with a person's response to certain drugs in relation to the therapeutic efficiency, clinical outcome, or even survival, and how they affect drug metabolism, transport, or clearance. Yet, since the incidence of these polymorphisms, being either single-point variations or small insertions/deletions, varies among different populations, a systematic collection and documentation of these variations is warranted, in order to facilitate implementation of pharmacogenomics in different populations. Here we review the existing electronic databases related to pharmacogenomics and pay particular attention in the description of the pharmacogenomics module Frequency of Inherited Disorders database (FINDbase), which documents curated allelic frequency data pertaining to 144 pharmacogenomics markers across 14 genes, representing approximately 87,000 individuals from 150 populations and ethnic groups worldwide. Long-term sustainability of these resources aims to contribute to the design, development, and implementation of pharmacogenomics testing towards the application of personalized approaches in medical treatment.
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Affiliation(s)
- Marianthi Georgitsi
- Department of Pharmacy, School of Health Sciences, University of Patras, Patras, Greece
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Patrinos GP, Smith TD, Howard H, Al-Mulla F, Chouchane L, Hadjisavvas A, Hamed SA, Li XT, Marafie M, Ramesar RS, Ramos FJ, de Ravel T, El-Ruby MO, Shrestha TR, Sobrido MJ, Tadmouri G, Witsch-Baumgartner M, Zilfalil BA, Auerbach AD, Carpenter K, Cutting GR, Dung VC, Grody W, Hasler J, Jorde L, Kaput J, Macek M, Matsubara Y, Padilla C, Robinson H, Rojas-Martinez A, Taylor GR, Vihinen M, Weber T, Burn J, Qi M, Cotton RGH, Rimoin D. Human Variome Project country nodes: documenting genetic information within a country. Hum Mutat 2012; 33:1513-9. [PMID: 22753370 DOI: 10.1002/humu.22147] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2012] [Accepted: 06/04/2012] [Indexed: 11/09/2022]
Abstract
The Human Variome Project (http://www.humanvariomeproject.org) is an international effort aiming to systematically collect and share information on all human genetic variation. The two main pillars of this effort are gene/disease-specific databases and a network of Human Variome Project Country Nodes. The latter are nationwide efforts to document the genomic variation reported within a specific population. The development and successful operation of the Human Variome Project Country Nodes are of utmost importance to the success of Human Variome Project's aims and goals because they not only allow the genetic burden of disease to be quantified in different countries, but also provide diagnosticians and researchers access to an up-to-date resource that will assist them in their daily clinical practice and biomedical research, respectively. Here, we report the discussions and recommendations that resulted from the inaugural meeting of the International Confederation of Countries Advisory Council, held on 12th December 2011, during the 2011 Human Variome Project Beijing Meeting. We discuss the steps necessary to maximize the impact of the Country Node effort for developing regional and country-specific clinical genetics resources and summarize a few well-coordinated genetic data collection initiatives that would serve as paradigms for similar projects.
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Affiliation(s)
- George P Patrinos
- Department of Pharmacy, School of Health Sciences, University of Patras, Patras, Greece.
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Patrinos GP, Al Aama J, Al Aqeel A, Al-Mulla F, Borg J, Devereux A, Felice AE, Macrae F, Marafie MJ, Petersen MB, Qi M, Ramesar RS, Zlotogora J, Cotton RGH. Recommendations for genetic variation data capture in developing countries to ensure a comprehensive worldwide data collection. Hum Mutat 2011; 32:2-9. [PMID: 21089065 PMCID: PMC3058135 DOI: 10.1002/humu.21397] [Citation(s) in RCA: 22] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
Developing countries have significantly contributed to the elucidation of the genetic basis of both common and rare disorders, providing an invaluable resource of cases due to large family sizes, consanguinity, and potential founder effects. Moreover, the recognized depth of genomic variation in indigenous African populations, reflecting the ancient origins of humanity on the African continent, and the effect of selection pressures on the genome, will be valuable in understanding the range of both pathological and nonpathological variations. The involvement of these populations in accurately documenting the extant genetic heterogeneity is more than essential. Developing nations are regarded as key contributors to the Human Variome Project (HVP; http://www.humanvariomeproject.org), a major effort to systematically collect mutations that contribute to or cause human disease and create a cyber infrastructure to tie databases together. However, biomedical research has not been the primary focus in these countries even though such activities are likely to produce economic and health benefits for all. Here, we propose several recommendations and guidelines to facilitate participation of developing countries in genetic variation data documentation, ensuring an accurate and comprehensive worldwide data collection. We also summarize a few well-coordinated genetic data collection initiatives that would serve as paradigms for similar projects. Hum Mutat 31:1–8, 2010. © 2010 Wiley-Liss, Inc.
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Björk BC. A study of innovative features in scholarly open access journals. J Med Internet Res 2011; 13:e115. [PMID: 22173122 PMCID: PMC3278101 DOI: 10.2196/jmir.1802] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2011] [Revised: 08/06/2011] [Accepted: 09/25/2011] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND The emergence of the Internet has triggered tremendous changes in the publication of scientific peer-reviewed journals. Today, journals are usually available in parallel electronic versions, but the way the peer-review process works, the look of articles and journals, and the rigid and slow publication schedules have remained largely unchanged, at least for the vast majority of subscription-based journals. Those publishing firms and scholarly publishers who have chosen the more radical option of open access (OA), in which the content of journals is freely accessible to anybody with Internet connectivity, have had a much bigger degree of freedom to experiment with innovations. OBJECTIVE The objective was to study how open access journals have experimented with innovations concerning ways of organizing the peer review, the format of journals and articles, new interactive and media formats, and novel publishing revenue models. METHODS The features of 24 open access journals were studied. The journals were chosen in a nonrandom manner from the approximately 7000 existing OA journals based on available information about interesting journals and include both representative cases and highly innovative outlier cases. RESULTS Most early OA journals in the 1990s were founded by individual scholars and used a business model based on voluntary work close in spirit to open-source development of software. In the next wave, many long-established journals, in particular society journals and journals from regions such as Latin America, made their articles OA when they started publishing parallel electronic versions. From about 2002 on, newly founded professional OA publishing firms using article-processing charges to fund their operations have emerged. Over the years, there have been several experiments with new forms of peer review, media enhancements, and the inclusion of structured data sets with articles. In recent years, the growth of OA publishing has also been facilitated by the availability of open-source software for journal publishing. CONCLUSIONS The case studies illustrate how a new technology and a business model enabled by new technology can be harnessed to find new innovative ways for the organization and content of scholarly publishing. Several recent launches of OA journals by major subscription publishers demonstrate that OA is rapidly gaining acceptance as a sustainable alternative to subscription-based scholarly publishing.
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Mitropoulou C, Webb AJ, Mitropoulos K, Brookes AJ, Patrinos GP. Locus-specific database domain and data content analysis: evolution and content maturation toward clinical use. Hum Mutat 2011; 31:1109-16. [PMID: 20672379 DOI: 10.1002/humu.21332] [Citation(s) in RCA: 37] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Genetic variation databases have become indispensable in many areas of health care. In addition, more and more experts are depositing published and unpublished disease-causing variants of particular genes into locus-specific databases (LSDBs). Some of these databases contain such extensive information that they have become known as knowledge bases. Here, we analyzed 1,188 LSDBs and their content for the presence or absence of 44 content criteria related to database features (general presentation, locus-specific information, database structure) and data content (data collection, summary table of variants, database querying). Our analyses revealed that several elements have helped to advance the field and reduce data heterogeneity, such as the development of specialized database management systems and the creation of data querying tools. We also identified a number of deficiencies, namely, the lack of detailed disease and phenotypic descriptions for each genetic variant and links to relevant patient organizations, which, if addressed, would allow LSDBs to better serve the clinical genetics community. We propose a structure, based on LSDBs and closely related repositories (namely, clinical genetics databases), which would contribute to a federated genetic variation browser and also allow the maintenance of variation data.
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Affiliation(s)
- Christina Mitropoulou
- Erasmus MC, Faculty of Medicine and Health Sciences, MGC-Department of Cell Biology and Genetics, Rotterdam, The Netherlands
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Georgitsi M, Viennas E, Gkantouna V, Christodoulopoulou E, Zagoriti Z, Tafrali C, Ntellos F, Giannakopoulou O, Boulakou A, Vlahopoulou P, Kyriacou E, Tsaknakis J, Tsakalidis A, Poulas K, Tzimas G, Patrinos GP. Population-specific documentation of pharmacogenomic markers and their allelic frequencies in FINDbase. Pharmacogenomics 2011; 12:49-58. [DOI: 10.2217/pgs.10.169] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023] Open
Abstract
Aims: Population and ethnic group-specific allele frequencies of pharmacogenomic markers are poorly documented and not systematically collected in structured data repositories. We developed the Frequency of Inherited Disorders Pharmacogenomics database (FINDbase-PGx), a separate module of the FINDbase, aiming to systematically document pharmacogenomic allele frequencies in various populations and ethnic groups worldwide. Materials & methods: We critically collected and curated 214 scientific articles reporting pharmacogenomic markers allele frequencies in various populations and ethnic groups worldwide. Subsequently, in order to host the curated data, support data visualization and data mining, we developed a website application, utilizing Microsoft™ PivotViewer software. Results: Curated allelic frequency data pertaining to 144 pharmacogenomic markers across 14 genes, representing approximately 87,000 individuals from 150 populations worldwide, are currently included in FINDbase-PGx. A user-friendly query interface allows for easy data querying, based on numerous content criteria, such as population, ethnic group, geographical region, gene, drug and rare allele frequency. Conclusion: FINDbase-PGx is a comprehensive database, which, unlike other pharmacogenomic knowledgebases, fulfills the much needed requirement to systematically document pharmacogenomic allelic frequencies in various populations and ethnic groups worldwide.
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Affiliation(s)
- Marianthi Georgitsi
- Department of Pharmacy, School of Health Sciences, University of Patras, Patras, Greece
| | - Emmanouil Viennas
- Department of Computer Engineering & Informatics, Faculty of Engineering, University of Patras, Patras, Greece
| | - Vassiliki Gkantouna
- Department of Computer Engineering & Informatics, Faculty of Engineering, University of Patras, Patras, Greece
| | | | - Zoi Zagoriti
- Department of Pharmacy, School of Health Sciences, University of Patras, Patras, Greece
| | - Christina Tafrali
- Department of Pharmacy, School of Health Sciences, University of Patras, Patras, Greece
| | - Fotios Ntellos
- Department of Pharmacy, School of Health Sciences, University of Patras, Patras, Greece
| | - Olga Giannakopoulou
- Department of Pharmacy, School of Health Sciences, University of Patras, Patras, Greece
| | - Athanassia Boulakou
- Department of Pharmacy, School of Health Sciences, University of Patras, Patras, Greece
| | - Panagiota Vlahopoulou
- Department of Pharmacy, School of Health Sciences, University of Patras, Patras, Greece
| | - Eva Kyriacou
- Department of Pharmacy, School of Health Sciences, University of Patras, Patras, Greece
| | - John Tsaknakis
- Department of Computer Engineering & Informatics, Faculty of Engineering, University of Patras, Patras, Greece
| | - Athanassios Tsakalidis
- Department of Computer Engineering & Informatics, Faculty of Engineering, University of Patras, Patras, Greece
| | - Konstantinos Poulas
- Department of Pharmacy, School of Health Sciences, University of Patras, Patras, Greece
| | - Giannis Tzimas
- Department of Computer Engineering & Informatics, Faculty of Engineering, University of Patras, Patras, Greece
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Georgitsi M, Viennas E, Antoniou DI, Gkantouna V, van Baal S, Petricoin EF, Poulas K, Tzimas G, Patrinos GP. FINDbase: a worldwide database for genetic variation allele frequencies updated. Nucleic Acids Res 2010; 39:D926-32. [PMID: 21113021 PMCID: PMC3013745 DOI: 10.1093/nar/gkq1236] [Citation(s) in RCA: 22] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
Frequency of INherited Disorders database (FIND base; http://www.findbase.org) records frequencies of causative genetic variations worldwide. Database records include the population and ethnic group or geographical region, the disorder name and the related gene, accompanied by links to any related external resources and the genetic variation together with its frequency in that population. In addition to the regular data content updates, we report the following significant advances: (i) the systematic collection and thorough documentation of population/ethnic group-specific pharmacogenomic markers allele frequencies for 144 markers in 14 genes of pharmacogenomic interest from different classes of drug-metabolizing enzymes and transporters, representing 150 populations and ethnic groups worldwide; (ii) the development of new data querying and visualization tools in the expanded FINDbase data collection, built around Microsoft's PivotViewer software (http://www.getpivot.com), based on Microsoft Silverlight technology (http://www.silverlight.net) that facilitates querying of large data sets and visualizing the results; and (iii) the establishment of the first database journal, by affiliating FINDbase with Human Genomics and Proteomics, a new open-access scientific journal, which would serve as a prime example of a non-profit model for sustainable database funding.
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Affiliation(s)
- Marianthi Georgitsi
- Department of Pharmacy, School of Health Sciences, Faculty of Engineering, University of Patras, Patras, Greece
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Kaput J, Cotton RGH, Hardman L, Watson M, Al Aqeel AI, Al-Aama JY, Al-Mulla F, Alonso S, Aretz S, Auerbach AD, Bapat B, Bernstein IT, Bhak J, Bleoo SL, Blöcker H, Brenner SE, Burn J, Bustamante M, Calzone R, Cambon-Thomsen A, Cargill M, Carrera P, Cavedon L, Cho YS, Chung YJ, Claustres M, Cutting G, Dalgleish R, den Dunnen JT, Díaz C, Dobrowolski S, dos Santos MRN, Ekong R, Flanagan SB, Flicek P, Furukawa Y, Genuardi M, Ghang H, Golubenko MV, Greenblatt MS, Hamosh A, Hancock JM, Hardison R, Harrison TM, Hoffmann R, Horaitis R, Howard HJ, Barash CI, Izagirre N, Jung J, Kojima T, Laradi S, Lee YS, Lee JY, Gil-da-Silva-Lopes VL, Macrae FA, Maglott D, Marafie MJ, Marsh SGE, Matsubara Y, Messiaen LM, Möslein G, Netea MG, Norton ML, Oefner PJ, Oetting WS, O'Leary JC, de Ramirez AMO, Paalman MH, Parboosingh J, Patrinos GP, Perozzi G, Phillips IR, Povey S, Prasad S, Qi M, Quin DJ, Ramesar RS, Richards CS, Savige J, Scheible DG, Scott RJ, Seminara D, Shephard EA, Sijmons RH, Smith TD, Sobrido MJ, Tanaka T, Tavtigian SV, Taylor GR, Teague J, Töpel T, Ullman-Cullere M, Utsunomiya J, van Kranen HJ, Vihinen M, Webb E, Weber TK, Yeager M, Yeom YI, Yim SH, Yoo HS. Planning the human variome project: the Spain report. Hum Mutat 2009; 30:496-510. [PMID: 19306394 PMCID: PMC5879779 DOI: 10.1002/humu.20972] [Citation(s) in RCA: 43] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Abstract
The remarkable progress in characterizing the human genome sequence, exemplified by the Human Genome Project and the HapMap Consortium, has led to the perception that knowledge and the tools (e.g., microarrays) are sufficient for many if not most biomedical research efforts. A large amount of data from diverse studies proves this perception inaccurate at best, and at worst, an impediment for further efforts to characterize the variation in the human genome. Because variation in genotype and environment are the fundamental basis to understand phenotypic variability and heritability at the population level, identifying the range of human genetic variation is crucial to the development of personalized nutrition and medicine. The Human Variome Project (HVP; http://www.humanvariomeproject.org/) was proposed initially to systematically collect mutations that cause human disease and create a cyber infrastructure to link locus specific databases (LSDB). We report here the discussions and recommendations from the 2008 HVP planning meeting held in San Feliu de Guixols, Spain, in May 2008.
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Affiliation(s)
- Jim Kaput
- Division of Personalised Nutrition and Medicine, FDA/National Center for Toxicological Research, Jefferson, Arkansas 72079, USA.
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