Evidence map›Paper›PMID 30595370›Full record

ArticleAmerican journal of human genetics2019

Leveraging Polygenic Functional Enrichment to Improve GWAS Power.

Gleb Kichaev, Gaurav Bhatia, Po-Ru Loh, Steven Gazal, Kathryn Burch, Malika K Freund, Armin Schoech, Bogdan Pasaniuc, Alkes L Price

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in American journal of human genetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 615 papers, 18 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
615citing papers in PubMed, 18 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

615 citing papers in PubMed, 18 syntheses or guidelines pooled it.

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555 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

9 authors.

Gleb KichaevInterdepartamental Program in Bioinformatics, University of California, Los Angeles, CA 90095, USA. Electronic address: gkichaev@ucla.edu.
Gaurav BhatiaDepartment of Epidemiology. Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA.
Po-Ru LohDepartment of Epidemiology. Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA; Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA.
Steven GazalDepartment of Epidemiology. Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA; Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA.
Kathryn BurchInterdepartamental Program in Bioinformatics, University of California, Los Angeles, CA 90095, USA.
Malika K FreundDepartment of Human Genetics, University of California, Los Angeles, CA 90095, USA.
Armin SchoechDepartment of Epidemiology. Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA; Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA.
Bogdan PasaniucInterdepartamental Program in Bioinformatics, University of California, Los Angeles, CA 90095, USA; Department of Human Genetics, University of California, Los Angeles, CA 90095, USA; Department Pathology and Laboratory Medicine, University of California, Los Angeles, CA 90095, USA.
Alkes L PriceDepartment of Epidemiology. Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA; Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA; Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA. Electronic address: aprice@hsph.harvard.edu.

Funding

Statistical methods for studies of rare variantsR01MH101244 · NIMH · HARVARD MEDICAL SCHOOL · PI Benjamin Michael Neale, ALKES L PRICE · 2013 to 2026
$9.4M
Statistical methods to localize disease heritability and identify biological mechanismsR01MH107649 · NIMH · BROAD INSTITUTE, INC. · PI NEALE, BENJAMIN MICHAEL · 2015 to 2018
$2.9M
Functionally specialized components of disease heritability in ENCODE dataU01HG009379 · NHGRI · HARVARD SCHOOL OF PUBLIC HEALTH · PI PRICE, ALKES L, RAYCHAUDHURI, SOUMYA · 2017 to 2021
$2.5M
Training Grant in Neurobehavioral GeneticsT32MH073526 · NIMH · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI BEARDEN, CARRIE E, GESCHWIND, DANIEL H · 2006 to 2020
$2.4M
Integrative approaches for mapping the genetic risk of complex traitsR01HG009120 · NHGRI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI PASANIUC, BOGDAN · 2017 to 2021
$2.3M
Biomedical Big Data Training GrantT32LM012424 · NLM · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI PELLEGRINI, MATTEO · 2016 to 2019
$1.0M
Medical Research Council MC_PC_17228Medical Research Council MC_QA137853NHGRI NIH HHS R01 HG009120NHGRI NIH HHS U01 HG009379NIMH NIH HHS R01 MH101244NIMH NIH HHS R01 MH107649NIMH NIH HHS T32 MH073526
6 · The paper itself

Abstract

Functional genomics data has the potential to increase GWAS power by identifying SNPs that have a higher prior probability of association. Here, we introduce a method that leverages polygenic functional enrichment to incorporate coding, conserved, regulatory, and LD-related genomic annotations into association analyses. We show via simulations with real genotypes that the method, functionally informed novel discovery of risk loci (FINDOR), correctly controls the false-positive rate at null loci and attains a 9%-38% increase in the number of independent associations detected at causal loci, depending on trait polygenicity and sample size. We applied FINDOR to 27 independent complex traits and diseases from the interim UK Biobank release (average N = 130K). Averaged across traits, we attained a 13% increase in genome-wide significant loci detected (including a 20% increase for disease traits) compared to unweighted raw p values that do not use functional data. We replicated the additional loci in independent UK Biobank and non-UK Biobank data, yielding a highly statistically significant replication slope (0.66-0.69) in each case. Finally, we applied FINDOR to the full UK Biobank release (average N = 416K), attaining smaller relative improvements (consistent with simulations) but larger absolute improvements, detecting an additional 583 GWAS loci. In conclusion, leveraging functional enrichment using our method robustly increases GWAS power.

Indexed as

Genome-Wide Association StudyCalibrationDatabases, GeneticDatasets as TopicFalse Positive ReactionsHumansMultifactorial InheritancePolymorphism, Single NucleotideProbabilityReproducibility of ResultsUnited Kingdomcomplex traitsfunctional genomicsGWAS

Identifiers

PMID30595370
PMCPMC6323418

What OpenQuestion holds

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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.