FINDbase: a worldwide database for genetic variation allele frequencies updated

Documentation of clinically relevant genomic biomarker allele frequencies in the next-generation FINDbase worldwide database

FINDbase (http://www.findbase.org) is a comprehensive data resource recording the prevalence of clinically relevant genomic variants in various populations worldwide, such as pathogenic variants underlying genetic disorders as well as pharmacogenomic biomarkers that can guide drug treatment. Here, we report significant new developments and technological advancements in the database architecture, leading to a completely revamped database structure, querying interface, accompanied with substantial extensions of data content and curation. In particular, the FINDbase upgrade further improves the user experience by introducing responsive features that support a wide variety of mobile and stationary devices, while enhancing computational runtime due to the use of a modern Javascript framework such as ReactJS. Data collection is significantly enriched, with the data records being divided in a Public and Private version, the latter being accessed on the basis of data contribution, according to the microattribution approach, while the front end was redesigned to support the new functionalities and querying tools. The abovementioned updates further enhance the impact of FINDbase, improve the overall user experience, facilitate further data sharing by microattribution, and strengthen the role of FINDbase as a key resource for personalized medicine applications and personalized public health.

Expanded national database collection and data coverage in the FINDbase worldwide database for clinically relevant genomic variation allele frequencies

FINDbase (http://www.findbase.org) is a comprehensive data repository that records the prevalence of clinically relevant genomic variants in various populations worldwide, such as pathogenic variants leading mostly to monogenic disorders and pharmacogenomics biomarkers. The database also records the incidence of rare genetic diseases in various populations, all in well-distinct data modules. Here, we report extensive data content updates in all data modules, with direct implications to clinical pharmacogenomics. Also, we report significant new developments in FINDbase, namely (i) the release of a new version of the ETHNOS software that catalyzes development curation of national/ethnic genetic databases, (ii) the migration of all FINDbase data content into 90 distinct national/ethnic mutation databases, all built around Microsoft's PivotViewer (http://www.getpivot.com) software (iii) new data visualization tools and (iv) the interrelation of FINDbase with DruGeVar database with direct implications in clinical pharmacogenomics. The abovementioned updates further enhance the impact of FINDbase, as a key resource for Genomic Medicine applications.

EPMA position paper in cancer: current overview and future perspectives

At present, a radical shift in cancer treatment is occurring in terms of predictive, preventive, and personalized medicine (PPPM). Individual patients will participate in more aspects of their healthcare. During the development of PPPM, many rapid, specific, and sensitive new methods for earlier detection of cancer will result in more efficient management of the patient and hence a better quality of life. Coordination of the various activities among different healthcare professionals in primary, secondary, and tertiary care requires well-defined competencies, implementation of training and educational programs, sharing of data, and harmonized guidelines. In this position paper, the current knowledge to understand cancer predisposition and risk factors, the cellular biology of cancer, predictive markers and treatment outcome, the improvement in technologies in screening and diagnosis, and provision of better drug development solutions are discussed in the context of a better implementation of personalized medicine. Recognition of the major risk factors for cancer initiation is the key for preventive strategies (EPMA J. 4(1):6, 2013). Of interest, cancer predisposing syndromes in particular the monogenic subtypes that lead to cancer progression are well defined and one should focus on implementation strategies to identify individuals at risk to allow preventive measures and early screening/diagnosis. Implementation of such measures is disturbed by improper use of the data, with breach of data protection as one of the risks to be heavily controlled. Population screening requires in depth cost-benefit analysis to justify healthcare costs, and the parameters screened should provide information that allow an actionable and deliverable solution, for better healthcare provision.

Variation ontology: annotator guide

Background

Systematic representation of information related to genetic and non-genetic variations is required to allow large scale studies, data mining and data integration, and to make it possible to reveal novel relationships between genotype and phenotype. Although lots of variation data is available it is often difficult to use due to lack of systematics.

Results

A novel ontology, Variation Ontology (VariO http://variationontology.org), was developed for annotation of effects, consequences and mechanisms of variations. In this article instructions are provided on how VariO annotations are made. The major levels for description are the three molecules, namely DNA, RNA and protein. They are further divided to four major sublevels: variation type, function, structure, and property, and further up to eight sublevels. VariO annotation summarizes existing knowledge about a variation and its effects and formalizes it so that computational analyses are efficient. The annotations should be made on as many levels as possible. VariO annotations are made in reference to normal states, which vary for each data item including e.g. reference sequences, wild type properties, and activities.

Conclusions

Detailed instructions together with examples are provided to indicate how VariO can be used for annotation of variations and their effects. A dedicated tool has been developed for annotation and will be further developed to cover also evidence for the annotations. VariO is suitable for annotation of data in many types of databases. As several different kinds of databases are in a process of adapting VariO annotations it is important to have guidelines to guarantee consistent annotation.

Developments in FINDbase worldwide database for clinically relevant genomic variation allele frequencies

FINDbase (http://www.findbase.org) aims to document frequencies of clinically relevant genomic variations, namely causative mutations and pharmacogenomic markers, worldwide. Each database record includes the population, ethnic group or geographical region, the disorder name and the related gene, accompanied by links to any related databases and the genetic variation together with its frequency in that population. Here, we report, in addition to the regular data content updates, significant developments in FINDbase, related to data visualization and querying, data submission, interrelation with other resources and a new module for genetic disease summaries. In particular, (i) we have developed new data visualization tools that facilitate data querying and comparison among different populations, (ii) we have generated a new FINDbase module, built around Microsoft’s PivotViewer (http://www.getpivot.com) software, based on Microsoft Silverlight technology (http://www.silverlight.net), that includes 259 genetic disease summaries from five populations, systematically collected from the literature representing the documented genetic makeup of these populations and (iii) the implementation of a generic data submission tool for every module currently available in FINDbase.

Updates of the HbVar database of human hemoglobin variants and thalassemia mutations

HbVar (http://globin.bx.psu.edu/hbvar) is one of the oldest and most appreciated locus-specific databases launched in 2001 by a multi-center academic effort to provide timely information on the genomic alterations leading to hemoglobin variants and all types of thalassemia and hemoglobinopathies. Database records include extensive phenotypic descriptions, biochemical and hematological effects, associated pathology and ethnic occurrence, accompanied by mutation frequencies and references. Here, we report updates to >600 HbVar entries, inclusion of population-specific data for 28 populations and 27 ethnic groups for α-, and β-thalassemias and additional querying options in the HbVar query page. HbVar content was also inter-connected with two other established genetic databases, namely FINDbase (http://www.findbase.org) and Leiden Open-Access Variation database (http://www.lovd.nl), which allows comparative data querying and analysis. HbVar data content has contributed to the realization of two collaborative projects to identify genomic variants that lie on different globin paralogs. Most importantly, HbVar data content has contributed to demonstrate the microattribution concept in practice. These updates significantly enriched the database content and querying potential, enhanced the database profile and data quality and broadened the inter-relation of HbVar with other databases, which should increase the already high impact of this resource to the globin and genetic database community.

Genetic databases in pharmacogenomics: the Frequency of Inherited Disorders Database (FINDbase)

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.

EasyLCMS: an asynchronous web application for the automated quantification of LC-MS data

Background

Downstream applications in metabolomics, as well as mathematical modelling, require data in a quantitative format, which may also necessitate the automated and simultaneous quantification of numerous metabolites. Although numerous applications have been previously developed for metabolomics data handling, automated calibration and calculation of the concentrations in terms of μmol have not been carried out. Moreover, most of the metabolomics applications are designed for GC-MS, and would not be suitable for LC-MS, since in LC, the deviation in the retention time is not linear, which is not taken into account in these applications. Moreover, only a few are web-based applications, which could improve stand-alone software in terms of compatibility, sharing capabilities and hardware requirements, even though a strong bandwidth is required. Furthermore, none of these incorporate asynchronous communication to allow real-time interaction with pre-processed results.

Findings

Here, we present EasyLCMS (http://www.easylcms.es/), a new application for automated quantification which was validated using more than 1000 concentration comparisons in real samples with manual operation. The results showed that only 1% of the quantifications presented a relative error higher than 15%. Using clustering analysis, the metabolites with the highest relative error distributions were identified and studied to solve recurrent mistakes.

Conclusions

EasyLCMS is a new web application designed to quantify numerous metabolites, simultaneously integrating LC distortions and asynchronous web technology to present a visual interface with dynamic interaction which allows checking and correction of LC-MS raw data pre-processing results. Moreover, quantified data obtained with EasyLCMS are fully compatible with numerous downstream applications, as well as for mathematical modelling in the systems biology field.

Institutional Profile: Golden Helix Institute of Biomedical Research: interdisciplinary research and educational activities in pharmacogenomics and personalized medicine

The Golden Helix Institute of Biomedical Research is an international nonprofit scientific organization with interdisciplinary research and educational activities in the field of genome medicine in Europe, Asia and Latin America. These activities are supervised by an international scientific advisory council, consisting of world leaders in the field of genomics and translational medicine. Research activities include the regional coordination of the Pharmacogenomics for Every Nation Initiative in Europe, in an effort to integrate pharmacogenomics in developing countries, the development of several national/ethnic genetic databases and related web services and the critical assessment of the impact of genetics and genomic medicine on society in various countries. Educational activities also include the organization of the Golden Helix Symposia(®), which are high-profile scientific research symposia in the field of personalized medicine and the Golden Helix Pharmacogenomics Days, an international educational activity focused on pharmacogenomics, as part of its international pharmacogenomics education and outreach efforts.

Microattribution and nanopublication as means to incentivize the placement of human genome variation data into the public domain

The advances in bioinformatics required to annotate human genomic variants and to place them in public data repositories have not kept pace with their discovery. Moreover, a law of diminishing returns has begun to operate both in terms of data publication and submission. Although the continued deposition of such data in the public domain is essential to maximize both their scientific and clinical utility, rewards for data sharing are few, representing a serious practical impediment to data submission. To date, two main strategies have been adopted as a means to encourage the submission of human genomic variant data: (1) database journal linkups involving the affiliation of a scientific journal with a publicly available database and (2) microattribution, involving the unambiguous linkage of data to their contributors via a unique identifier. The latter could in principle lead to the establishment of a microcitation-tracking system that acknowledges individual endeavor and achievement. Both approaches could incentivize potential data contributors, thereby encouraging them to share their data with the scientific community. Here, we summarize and critically evaluate approaches that have been proposed to address current deficiencies in data attribution and discuss ways in which they could become more widely adopted as novel scientific publication modalities.

Human Variome Project country nodes: documenting genetic information within a country

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.

Population-ethnic group specific genome variation allele frequency data: a querying and visualization journey

National/ethnic mutation databases aim to document the genetic heterogeneity in various populations and ethnic groups worldwide. We have previously reported the development and upgrade of FINDbase (www.findbase.org), a database recording causative mutations and pharmacogenomic marker allele frequencies in various populations around the globe. Although this database has recently been upgraded, we continuously try to enhance its functionality by providing more advanced visualization tools that would further assist effective data querying and comparisons. We are currently experimenting in various visualization techniques on the existing FINDbase causative mutation data collection aiming to provide a dynamic research tool for the worldwide scientific community. We have developed an interactive web-based application for population-based mutation data retrieval. It supports sophisticated data exploration allowing users to apply advanced filtering criteria upon a set of multiple views of the underlying data collection and enables browsing the relationships between individual datasets in a novel and meaningful way.