Evidence map›Paper›PMID 21115973›Full record

ReviewGenetics2011

Progress and promise of genome-wide association studies for human complex trait genetics.

Barbara E Stranger, Eli A Stahl, Towfique Raj

Abstract readReview
In one paragraph

Review in Genetics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 269 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
269citing papers in PubMed, 6 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

269 citing papers in PubMed, 6 syntheses or guidelines pooled it.

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  5. Imputing Phenotypes for Genome-wide Association Studies.American journal of human genetics · 2016
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209 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

3 authors.

Barbara E StrangerDivision of Genetics, Brigham and Women's Hospital, Boston, Massachusetts 02115, USA. bstranger@rics.bwh.harvard.edu
Eli A Stahl
Towfique Raj

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Enormous progress in mapping complex traits in humans has been made in the last 5 yr. There has been early success for prevalent diseases with complex phenotypes. These studies have demonstrated clearly that, while complex traits differ in their underlying genetic architectures, for many common disorders the predominant pattern is that of many loci, individually with small effects on phenotype. For some traits, loci of large effect have been identified. For almost all complex traits studied in humans, the sum of the identified genetic effects comprises only a portion, generally less than half, of the estimated trait heritability. A variety of hypotheses have been proposed to explain why this might be the case, including untested rare variants, and gene-gene and gene-environment interaction. Effort is currently being directed toward implementation of novel analytic approaches and testing rare variants for association with complex traits using imputed variants from the publicly available 1000 Genomes Project resequencing data and from direct resequencing of clinical samples. Through integration with annotations and functional genomic data as well as by in vitro and in vivo experimentation, mapping studies continue to characterize functional variants associated with complex traits and address fundamental issues such as epistasis and pleiotropy. This review focuses primarily on the ways in which genome-wide association studies (GWASs) have revolutionized the field of human quantitative genetics.

Indexed as

Genome-Wide Association StudyAnimalsChromosome MappingGenetic Predisposition to DiseaseHumansModels, GeneticMultifactorial InheritancePolymorphism, Single NucleotideQuantitative Trait Loci

Identifiers

PMID21115973
PMCPMC3030483

What OpenQuestion holds

Textmetadata
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.