Evidence map›Paper›PMID 26189819›Full record

ArticleAmerican journal of human genetics2015

Leveraging Functional-Annotation Data in Trans-ethnic Fine-Mapping Studies.

Gleb Kichaev, Bogdan Pasaniuc

Erratum issuedAbstract read
In one paragraph

Article in American journal of human genetics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 142 papers, 15 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
142citing papers in PubMed, 15 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

142 citing papers in PubMed, 15 syntheses or guidelines pooled it.

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82 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

  • Erratum issued
5 · Who and what money

Authors and funding

2 authors.

Gleb KichaevBioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA 90095, USA.
Bogdan PasaniucBioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA 90095, USA; Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA; Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA. Electronic address: pasaniuc@ucla.edu.

Funding

STATISTICAL METHODS FOR GENE MAPPINGR01GM053275 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI LANGE, KENNETH L · 1995 to 2019
$9.3M
Methods for Genome-wide Association Studies in Admixed PopulationsR01HG006399 · NHGRI · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI PRICE, ALKES L · 2011 to 2024
$6.3M
Prioritizing follow-up of GWAS loci using genetic and functional annotation dataR21CA182821 · NCI · UNIVERSITY OF WASHINGTON · PI LINDSTROEM, SARA · 2014 to 2015
$395k
NCI NIH HHS R21 CA182821NCI NIH HHS R21-CA182821NHGRI NIH HHS R01 HG006399NHGRI NIH HHS R01-HG006399NIGMS NIH HHS R01 GM053275NIGMS NIH HHS R01-GM53275
6 · The paper itself

Abstract

Localization of causal variants underlying known risk loci is one of the main research challenges following genome-wide association studies. Risk loci are typically dissected through fine-mapping experiments in trans-ethnic cohorts for leveraging the variability in the local genetic structure across populations. More recent works have shown that genomic functional annotations (i.e., localization of tissue-specific regulatory marks) can be integrated for increasing fine-mapping performance within single-population studies. Here, we introduce methods that integrate the strength of association between genotype and phenotype, the variability in the genetic backgrounds across populations, and the genomic map of tissue-specific functional elements to increase trans-ethnic fine-mapping accuracy. Through extensive simulations and empirical data, we have demonstrated that our approach increases fine-mapping resolution over existing methods. We analyzed empirical data from a large-scale trans-ethnic rheumatoid arthritis (RA) study and showed that the functional genetic architecture of RA is consistent across European and Asian ancestries. In these data, we used our proposed methods to reduce the average size of the 90% credible set from 29 variants per locus for standard non-integrative approaches to 22 variants.

Indexed as

Genetic VariationModels, GeneticArthritis, RheumatoidBayes TheoremChromosome MappingEthnicityGenetics, PopulationHumansMolecular Sequence AnnotationRisk Assessment

Identifiers

PMID26189819
PMCPMC4573268

What OpenQuestion holds

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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.