Population-Specific Documentation of Pharmacogenomic Markers and Their Allelic Frequencies in Findbase

Georgitsi, Marianthi; Viennas, Emmanouil; Gkantouna, Vassiliki; Christodoulopoulou, Elena; Zagoriti, Zoi; Tafrali, Christina; Ntellos, Fotios; Giannakopoulou, Olga; Boulakou, Athanassia; Vlahopoulou, Panagiota; Kyriacou, Eva; Tsaknakis, John; Tsakalidis, A.; Poulas, Konstantinos; Tzimas, Giannis; Patrinos, George P.

doi:10.2217/pgs.10.169

Cited by 28 publications

(19 citation statements)

References 25 publications

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“…Candidate hosts are the pharmacogenomic biomarkers module of FINDbase database [8] or other electronic tools aiming to provide the pharmacogenomics user communities, namely biomedical researchers, physicians and healthcare providers, and regulatory authorities with innovative solutions to translate pharmacogenomics research findings into clinical reality.…”

Section: Resultsmentioning

confidence: 99%

DruGeVar: An Online Resource Triangulating Drugs with Genes and Genomic Biomarkers for Clinical Pharmacogenomics

Dalabira¹,

Viennas²,

Daki³

et al. 2014

Public Health Genomics

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Background/Aims: Pharmacogenomics aims to rationalize drug use by minimizing drug toxicity and/or by increasing drug efficacy. A large number of genomic markers have been correlated with variable drug responses and severity of adverse drug reactions. Although a number of these drugs bear pharmacogenomic information in their labels - approved by regulatory agencies - and comprehensive drug/gene lists exist online, information related to the respective pharmacogenomic biomarkers is currently missing from such lists. Methods: We extracted information from the published literature and online resources and developed DruGeVar (http://drugevar.genomicmedicinealliance.org), an online resource triangulating drugs with genes and pharmacogenomic biomarkers in an effort to build a comprehensive database that could serve clinical pharmacogenomics. Results and Conclusions: A user-friendly data querying and visualization interface allows users to formulate simple and complex queries. Such a database would be readily applicable as a stand-alone resource or a plug-in module for other databases.

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Section: Resultsmentioning

confidence: 99%

DruGeVar: An Online Resource Triangulating Drugs with Genes and Genomic Biomarkers for Clinical Pharmacogenomics

Dalabira¹,

Viennas²,

Daki³

et al. 2014

Public Health Genomics

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“…In addition, the FINDbase-PGx database [15] was searched for pharmacogenetic alleles identified in Jewish populations.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Like other CYP450 genes, common and rare CYP2C19 variants have been identified in various populations, which are catalogued by the Human Cytochrome P450 (CYP) Allele Nomenclature Committee [76]. Many of these encode reduced or complete loss of function, and their frequencies can also differ between racial and ethnic groups [15, 37, 38, 77, 78]. For example, CYP2C19*2 (c.681G>A) and *3 (p.W212X) are the most commonly studied CYP2C19 loss-of-function alleles with average multi-ethnic allele frequencies of ~18% and ~2%, respectively; however, *3 is more prevalent in Asian populations (~9%) [34, 37, 79, 80].…”

Section: Jewish Pharmacogeneticsmentioning

confidence: 99%

Pharmacogenetics in Jewish populations

Yao

Peter

Scott

2014

Drug Metabolism and Drug Interactions

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Spanning over 2000 years, the Jewish population has a long history of migration, population bottlenecks, expansions, and geographical isolation, which has resulted in a unique genetic architecture among the Jewish people. As such, many Mendelian disease genes and founder mutations for autosomal recessive diseases have been discovered in several Jewish groups, which have prompted recent genomic studies in the Jewish population on common disease susceptibility and other complex traits. Although few studies on the genetic determinants of drug response variability have been reported in the Jewish population, a number of unique pharmacogenetic variants have been discovered that are more common in Jewish populations than in other major racial groups. Notable examples identified in the Ashkenazi Jewish (AJ) population include the vitamin K epoxide reductase complex subunit 1 (VKORC1) c.106G>T (p.D36Y) variant associated with high warfarin dosing requirements and the recently reported cytochrome P450 2C19 (CYP2C19) allele, CYP2C19*4B, that harbors both loss-of-function [*4 (c.1A>G)] and increased-function [*17 (c.−806C>T)] variants on the same haplotype. These data are encouraging in that like other ethnicities and subpopulations, the Jewish population likely harbors numerous pharmacogenetic variants that are uncommon or absent in other larger racial groups and ethnicities. In addition to unique variants, common multi-ethnic variants in key drug metabolism genes (e.g., ABCB1, CYP2C8, CYP2C9, CYP2C19, CYP2D6, NAT2) have also been detected in the AJ and other Jewish groups. This review aims to summarize the currently available pharmacogenetics literature and discuss future directions for related research with this unique population.

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“…In [13], two mining tools were developed, Bio Search Engine which is a text mining tool working with biomedical literature acquired from PubMed and Genome-Based Population Clustering tool which extracts knowledge from data acquired from FINDbase [8,20,21]. FINDbase 2 is an online resource documenting frequencies of pathogenic genetic variations leading to inherited disorders in various populations worldwide.…”

Section: Introductionmentioning

confidence: 99%

Mining Biological Data on the Cloud – A MapReduce Approach

Ioannou

Nodarakis

Sioutas

et al. 2014

IFIP Advances in Information and Communication Technology

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Abstract. During last decades, bioinformatics has proven to be an emerging field of research leading to the development of a wide variety of applications. The primary goal of bioinformatics is to detect useful knowledge hidden under large volumes biological and biomedical data, gain a greater insight into their relationships and, therefore, enhance the discovery and the comprehension of biological processes. To achieve this, a great number of text mining techniques have been developed that efficiently manage and disclose meaningful patterns and correlations from biological and biomedical data repositories. However, as the volume of data grows rapidly these techniques cannot cope with the computational burden that is produced since they apply only in centralized environments. Consequently, a turn into distributed and parallel solutions is indispensable. In the context of this work, we propose an efficient and scalable solution, in the MapReduce framework, for mining and analyzing biological and biomedical data.

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Population-Specific Documentation of Pharmacogenomic Markers and Their Allelic Frequencies in Findbase

Abstract: 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.

Cited by 28 publications

References 25 publications

DruGeVar: An Online Resource Triangulating Drugs with Genes and Genomic Biomarkers for Clinical Pharmacogenomics

DruGeVar: An Online Resource Triangulating Drugs with Genes and Genomic Biomarkers for Clinical Pharmacogenomics

Pharmacogenetics in Jewish populations

Mining Biological Data on the Cloud – A MapReduce Approach

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