Evidence map›Paper›PMID 35365203›Full record

SynthesisBMC medical genomics2022

The landscape of GWAS validation; systematic review identifying 309 validated non-coding variants across 130 human diseases.

Ammar J Alsheikh, Sabrina Wollenhaupt, Emily A King, Jonas Reeb, Sujana Ghosh, Lindsay R Stolzenburg, Saleh Tamim, Jozef Lazar, J Wade Davis, Howard J Jacob

Abstract readSystematic Review
In one paragraph

Synthesis in BMC medical genomics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
46citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

46 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. UnlockingNAR genomics and bioinformatics · 2026
    Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Mechanoepigenetics in musculoskeletal disease.Osteoarthritis and cartilage · 2026
    Review
  10. Article
  11. Genetic variants reshape the mScientific reports · 2025
    Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Review
  17. Review
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Ammar J AlsheikhGenomics Research Center, AbbVie Inc, North Chicago, Illinois, 60064, USA. ammaralsheik@gmail.com.ORCID 0000-0001-7125-0144
Sabrina WollenhauptInformation Research, AbbVie Deutschland GmbH & Co. KG, 67061, Knollstrasse, Ludwigshafen, Germany.
Emily A KingGenomics Research Center, AbbVie Inc, North Chicago, Illinois, 60064, USA.
Jonas ReebInformation Research, AbbVie Deutschland GmbH & Co. KG, 67061, Knollstrasse, Ludwigshafen, Germany.
Sujana GhoshGenomics Research Center, AbbVie Inc, North Chicago, Illinois, 60064, USA.
Lindsay R StolzenburgGenomics Research Center, AbbVie Inc, North Chicago, Illinois, 60064, USA.
Saleh TamimGenomics Research Center, AbbVie Inc, North Chicago, Illinois, 60064, USA.
Jozef LazarGenomics Research Center, AbbVie Inc, North Chicago, Illinois, 60064, USA.
J Wade DavisGenomics Research Center, AbbVie Inc, North Chicago, Illinois, 60064, USA.
Howard J JacobGenomics Research Center, AbbVie Inc, North Chicago, Illinois, 60064, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe remarkable growth of genome-wide association studies (GWAS) has created a critical need to experimentally validate the disease-associated variants, 90% of which involve non-coding variants.

methodsTo determine how the field is addressing this urgent need, we performed a comprehensive literature review identifying 36,676 articles. These were reduced to 1454 articles through a set of filters using natural language processing and ontology-based text-mining. This was followed by manual curation and cross-referencing against the GWAS catalog, yielding a final set of 286 articles.

resultsWe identified 309 experimentally validated non-coding GWAS variants, regulating 252 genes across 130 human disease traits. These variants covered a variety of regulatory mechanisms. Interestingly, 70% (215/309) acted through cis-regulatory elements, with the remaining through promoters (22%, 70/309) or non-coding RNAs (8%, 24/309). Several validation approaches were utilized in these studies, including gene expression (n = 272), transcription factor binding (n = 175), reporter assays (n = 171), in vivo models (n = 104), genome editing (n = 96) and chromatin interaction (n = 33).

conclusionsThis review of the literature is the first to systematically evaluate the status and the landscape of experimentation being used to validate non-coding GWAS-identified variants. Our results clearly underscore the multifaceted approach needed for experimental validation, have practical implications on variant prioritization and considerations of target gene nomination. While the field has a long way to go to validate the thousands of GWAS associations, we show that progress is being made and provide exemplars of validation studies covering a wide variety of mechanisms, target genes, and disease areas.

Indexed as

Genome-Wide Association StudyRegulatory Sequences, Nucleic AcidHumansPhenotypePromoter Regions, GeneticExperimental validationFunctional variantGWASNon-codingSystematic review

Identifiers

PMID35365203
PMCPMC8973751

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.