Evidence map›Paper›PMID 27346688›Full record

ArticleAmerican journal of human genetics2016

Contrasting the Genetic Architecture of 30 Complex Traits from Summary Association Data.

Huwenbo Shi, Gleb Kichaev, Bogdan Pasaniuc

Abstract read
In one paragraph

Article in American journal of human genetics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 233 papers, 10 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
233citing papers in PubMed, 10 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

233 citing papers in PubMed, 10 syntheses or guidelines pooled it.

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  14. Adaptation: by giant leaps or many tiny steps?Nature reviews. Genetics · 2026
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  17. Unravelling the genetic architecture of cerebral small vessel disease in the context of stroke.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2026
    Review
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173 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.

Huwenbo ShiBioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA 90024, USA.
Gleb KichaevBioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA 90024, USA.
Bogdan PasaniucBioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA 90024, USA; Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90024, USA; Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90024, USA. Electronic address: pasaniuc@ucla.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Variance-component methods that estimate the aggregate contribution of large sets of variants to the heritability of complex traits have yielded important insights into the genetic architecture of common diseases. Here, we introduce methods that estimate the total trait variance explained by the typed variants at a single locus in the genome (local SNP heritability) from genome-wide association study (GWAS) summary data while accounting for linkage disequilibrium among variants. We applied our estimator to ultra-large-scale GWAS summary data of 30 common traits and diseases to gain insights into their local genetic architecture. First, we found that common SNPs have a high contribution to the heritability of all studied traits. Second, we identified traits for which the majority of the SNP heritability can be confined to a small percentage of the genome. Third, we identified GWAS risk loci where the entire locus explains significantly more variance in the trait than the GWAS reported variants. Finally, we identified loci that explain a significant amount of heritability across multiple traits.

Indexed as

Genome-Wide Association StudyModels, GeneticPhenotypeDatasets as TopicGenetic Predisposition to DiseaseHumansLinkage DisequilibriumMultifactorial InheritancePolymorphism, Single NucleotideQuantitative Trait Loci

Identifiers

PMID27346688
PMCPMC5005444

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.