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. 2019 Jan 7:2:9.
doi: 10.1038/s42003-018-0261-x. eCollection 2019.

A scientometric review of genome-wide association studies

Melinda C Mills  1 , Charles Rahal  1
Affiliations

A scientometric review of genome-wide association studies

Melinda C Mills et al. Commun Biol. .

Abstract

This scientometric review of genome-wide association studies (GWAS) from 2005 to 2018 (3639 studies; 3508 traits) reveals extraordinary increases in sample sizes, rates of discovery and traits studied. A longitudinal examination shows fluctuating ancestral diversity, still predominantly European Ancestry (88% in 2017) with 72% of discoveries from participants recruited from three countries (US, UK, Iceland). US agencies, primarily NIH, fund 85% and women are less often senior authors. We generate a unique GWAS H-Index and reveal a tight social network of prominent authors and frequently used data sets. We conclude with 10 evidence-based policy recommendations for scientists, research bodies, funders, and editors.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
The growth of GWAS, 2007–2017. The upper panel shows the number of study accessions published per quarter over time colored according to sample size to show the growth of larger (100,001 ≤ N) GWAS. The lower left panel shows the strong positive correlation between the number of associations found and the number of participants used in GWAS over time. The lower right panel shows the growth in the number of unique traits examined as well as the number of unique journals publishing GWAS over time. 2007–2017 is selected since only 10 entries occurred before 2007. Each panel contains full calendar years only. Source: NHGRI-EBI GWAS Catalog
Fig. 2
Fig. 2
GWAS Participant Ancestry over Time, 2007–2017. The main panel shows a disaggregation of our broad ancestral categories field, which is a direct mapping from the 17 broad ancestral categories identified in the Catalog. We drop all rows where any proportion of the ancestry is not recorded, and for combinations of ancestries (e.g., European and African) we create a new field: Other/Mixed. The inset aggregates this across the entire sample but partitions the data across discovery and replication phases. 2007–2017 is selected since only 10 entries occurred before 2007 and we have complete information for the year 2017. Source: NHGRI-EBI GWAS Catalog and author mapping
Fig. 3
Fig. 3
A Choropleth Map of the Concentration of GWAS Participant Recruitment. A choropleth map (Robinson projection) detailing the geographic recruitment of GWAS participants. Source: NHGRI-EBI GWAS Catalog, Natural Earth (v4.0.0) and the CIA World Factbook. Replication material provides a per-capita population adjusted version
Fig. 4
Fig. 4
Distribution of Funder Acknowledgments by Ancestry and Trait Categories. Heatmap showing the distribution of Grant Contributions of the 10 most frequently observed agencies tabulated against our synthetic broader ancestral category term and Parent Term fields (higher level trait or disease categories). All agencies are based in the US, other than the Medical Research Council (MRC) and Wellcome Trust. In the US, other than Public Health Service, the rest are part of the National Institute of Health (NIH). Replication material provides an alternative mapping to Broad EFO category where comma separated entries are not split but dropped. Source: NHGRI-EBI GWAS Catalog and the PubMed database
See this image and copyright information in PMC

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