Evidence map›Paper›PMID 21747404›Full record

ReviewNature reviews. Genetics2011

Epigenome-wide association studies for common human diseases.

Vardhman K Rakyan, Thomas A Down, David J Balding, Stephan Beck

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Nature reviews. Genetics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 671 papers, 17 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
671citing papers in PubMed, 17 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

671 citing papers in PubMed, 17 syntheses or guidelines pooled it.

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  4. A Systematic Review of the Application of Graph Neural Networks to Extract Candidate Genes and Biological Associations.American journal of medical genetics. Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics · 2025
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611 more citing papers are in PubMed but not listed here.

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

4 authors.

Vardhman K RakyanBlizard Institute of Cell and Molecular Science, Barts and The London School of Medicine and Dentistry, Queen Mary, University of London, London, UK. v.rakyan@qmul.ac.uk
Thomas A Down
David J Balding
Stephan Beck

Funding

Wellcome Trust 084071
6 · The paper itself

Abstract

Despite the success of genome-wide association studies (GWASs) in identifying loci associated with common diseases, a substantial proportion of the causality remains unexplained. Recent advances in genomic technologies have placed us in a position to initiate large-scale studies of human disease-associated epigenetic variation, specifically variation in DNA methylation. Such epigenome-wide association studies (EWASs) present novel opportunities but also create new challenges that are not encountered in GWASs. We discuss EWAS design, cohort and sample selections, statistical significance and power, confounding factors and follow-up studies. We also discuss how integration of EWASs with GWASs can help to dissect complex GWAS haplotypes for functional analysis.

Indexed as

Genetic Predisposition to DiseaseBiomarkersDNA MethylationEpigenomicsGene Expression ProfilingGenetic VariationGenome, HumanGenome-Wide Association StudyHaplotypesHumansOligonucleotide Array Sequence AnalysisSequence Analysis, DNABiomarkers

Identifiers

PMID21747404
PMCPMC3508712

What OpenQuestion holds

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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.