Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2021 Jan 8;49(D1):D1311-D1320.
doi: 10.1093/nar/gkaa840.

Open Targets Genetics: systematic identification of trait-associated genes using large-scale genetics and functional genomics

Maya Ghoussaini  1   2 , Edward Mountjoy  1   2 , Miguel Carmona  2   3 , Gareth Peat  2   3 , Ellen M Schmidt  1   2 , Andrew Hercules  2   3 , Luca Fumis  2   3 , Alfredo Miranda  2   3 , Denise Carvalho-Silva  2   3 , Annalisa Buniello  2   3 , Tony Burdett  2   3 , James Hayhurst  2   3 , Jarrod Baker  2   3 , Javier Ferrer  2   3 , Asier Gonzalez-Uriarte  2   3 , Simon Jupp  2   3 , Mohd Anisul Karim  1   2 , Gautier Koscielny  2   4 , Sandra Machlitt-Northen  2   4 , Cinzia Malangone  2   3 , Zoe May Pendlington  2   3 , Paola Roncaglia  2   3 , Daniel Suveges  2   3 , Daniel Wright  1   2 , Olga Vrousgou  2   3 , Eliseo Papa  2   5 , Helen Parkinson  2   3 , Jacqueline A L MacArthur  3 , John A Todd  6 , Jeffrey C Barrett  1   2 , Jeremy Schwartzentruber  1   2 , David G Hulcoop  2   4 , David Ochoa  2   3 , Ellen M McDonagh  1   3 , Ian Dunham  1   2   3
Affiliations

Open Targets Genetics: systematic identification of trait-associated genes using large-scale genetics and functional genomics

Maya Ghoussaini et al. Nucleic Acids Res. .

Abstract

Open Targets Genetics (https://genetics.opentargets.org) is an open-access integrative resource that aggregates human GWAS and functional genomics data including gene expression, protein abundance, chromatin interaction and conformation data from a wide range of cell types and tissues to make robust connections between GWAS-associated loci, variants and likely causal genes. This enables systematic identification and prioritisation of likely causal variants and genes across all published trait-associated loci. In this paper, we describe the public resources we aggregate, the technology and analyses we use, and the functionality that the portal offers. Open Targets Genetics can be searched by variant, gene or study/phenotype. It offers tools that enable users to prioritise causal variants and genes at disease-associated loci and access systematic cross-disease and disease-molecular trait colocalization analysis across 92 cell types and tissues including the eQTL Catalogue. Data visualizations such as Manhattan-like plots, regional plots, credible sets overlap between studies and PheWAS plots enable users to explore GWAS signals in depth. The integrated data is made available through the web portal, for bulk download and via a GraphQL API, and the software is open source. Applications of this integrated data include identification of novel targets for drug discovery and drug repurposing.

PubMed Disclaimer

Figures

Figure 1.
Figure 1.
Data resources, ingestion process, data analyses and accessibility of the Open Target Genetics Portal. (A) The datasets ingested into Open Targets Genetics, (B) the data ingest and mapping processes, (C) statistical genetics analyses carried out, (D) the Locus to Gene pipeline (L2G), (E) accessibility options for users. Abbreviations: API; Application Programming Interface, EFO; experimental factor ontology, EMBL-EBI; European Molecular Biology Laboratory – European Bioinformatics Institute, LD; linkage disequilibrium, FTP; file transfer protocol.
Figure 2.
Figure 2.
Study-trait page. The study-trait page in the Open Targets Portal for the associated trait inflammatory bowel disease from the study (22). Abbreviations: IBD; inflammatory bowel disease, ID; identifier, GWAS; Genome-wide association study, LD; linkage disequilibrium, L2G; locus-to-gene, SNP; single nucleotide polymorphism.
Figure 3.
Figure 3.
Variant page. (A) Each variant in the Open Targets Genetics Portal is represented with a standardised identifier of: chromosome_chromosomal location (Build GRCh38)_reference allele_alternative allele. Overview information is provided for the variant at the top of the page, such as allele frequency and predicted functional consequence. (B) Assigned genes using the Variant to Gene score and expression data evidence for the link between the variant and gene. (C) PheWAS plot and data. Abbreviations: eQTL; expression quantitative trait loci, LD; linkage disequilibrium, PheWAS; phenome wide association study, V2G; variant to gene.
Figure 4.
Figure 4.
Gene page. (A) Overview of the gene and chromosome location (Build GRCh38), with links to the Open Targets Platform and other key data resources for relevant information. (B) GWAS studies or traits associated with the gene from the Locus-to-Gene analysis pipeline. (C) GWAS studies or traits associated with molecular quantitative trait loci for the gene, based on colocalization analysis evidence. Abbreviations: GWAS; Genome-wide association study, QTLs; quantitative trait loci, L2G; locus-to-gene.
Figure 5.
Figure 5.
Study-locus page. An example of the gene prioritisation page for the lead variant 2_181443625_A_G and the inflammatory bowel disease GWAS24. Gene prioritisation results from (A) the locus-to-gene analysis pipeline and (B) colocalisation analysis. (C) A heatmap view of genes that colocalise at this locus. (D) GWAS study colocalisation. (E) Credible set overlap. Abbreviations: GWAS; Genome-wide association study, IBD; inflammatory bowel disease, L2G; locus-to-gene, OR; odds ratio, QTLs; quantitative trait loci.
See this image and copyright information in PMC

References

    1. Hay M., Thomas D.W., Craighead J.L., Economides C., Rosenthal J.. Clinical development success rates for investigational drugs. Nat. Biotechnol. 2014; 32:40–51. - PubMed
    1. DiMasi J.A., Grabowski H.G., Hansen R.W.. Innovation in the pharmaceutical industry: new estimates of R&D costs. J. Health Econ. 2016; 47:20–33. - PubMed
    1. Nelson M.R, Tipney H., Painter J.L., Shen J., Nicoletti P., Shen Y., Floratos A., Sham P.C., Li M.J., Wang J. et al. .. The support of human genetic evidence for approved drug indications. Nat. Genet. 2019; 47:856–860. - PubMed
    1. King E.A., Davis J.W., Degner J.F.. Are drug targets with genetic support twice as likely to be approved? Revised estimates of the impact of genetic support for drug mechanisms on the probability of drug approval. PLos Genet. 2019; 15:e1008489. - PMC - PubMed
    1. Carvalho-Silva D., Pierleoni A., Pignatelli M., Ong C., Fumis L., Karamanis N., Carmona M., Faulconbridge A., Hercules A., McAuley E. et al. .. Open Targets Platform: new developments and updates two years on. Nucleic Acids Res. 2019; 47:D1056–D1065. - PMC - PubMed

Publication types

MeSH terms