Evidence map›Paper›PMID 39322778›Full record

ArticleNature genetics2024

Yield of genetic association signals from genomes, exomes and imputation in the UK Biobank.

Sheila M Gaynor, Tyler Joseph, Xiaodong Bai, Yuxin Zou, Boris Boutkov, Evan K Maxwell, Olivier Delaneau, Robin J Hofmeister, Olga Krasheninina, Suganthi Balasubramanian and 11 more

Abstract read
In one paragraph

Article in Nature genetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 2 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

20 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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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

21 authors.

Sheila M Gaynor *Regeneron Genetics Center, Tarrytown, NY, USA. sheila.gaynor@regeneron.com.ORCID http://orcid.org/0000-0002-7869-5223
Tyler Joseph *Regeneron Genetics Center, Tarrytown, NY, USA.
Xiaodong BaiRegeneron Genetics Center, Tarrytown, NY, USA.
Yuxin ZouRegeneron Genetics Center, Tarrytown, NY, USA.
Boris BoutkovRegeneron Genetics Center, Tarrytown, NY, USA.
Evan K MaxwellRegeneron Genetics Center, Tarrytown, NY, USA.ORCID http://orcid.org/0000-0002-7325-7531
Olivier DelaneauRegeneron Genetics Center, Tarrytown, NY, USA.ORCID http://orcid.org/0000-0002-3906-8446
Robin J HofmeisterDepartment of Computational Biology, University of Lausanne, Lausanne, Switzerland.
Olga KrashenininaRegeneron Genetics Center, Tarrytown, NY, USA.
Suganthi BalasubramanianRegeneron Genetics Center, Tarrytown, NY, USA.ORCID http://orcid.org/0000-0003-2243-5948
Anthony MarckettaRegeneron Genetics Center, Tarrytown, NY, USA.
Joshua BackmanRegeneron Genetics Center, Tarrytown, NY, USA.ORCID http://orcid.org/0000-0001-7262-0880
Regeneron Genetics Center
Jeffrey G ReidRegeneron Genetics Center, Tarrytown, NY, USA.ORCID http://orcid.org/0000-0001-8645-4713
John D OvertonRegeneron Genetics Center, Tarrytown, NY, USA.
Luca A LottaRegeneron Genetics Center, Tarrytown, NY, USA.ORCID http://orcid.org/0000-0002-2619-5956
Jonathan MarchiniRegeneron Genetics Center, Tarrytown, NY, USA.ORCID http://orcid.org/0000-0003-0610-8322
William J SalernoRegeneron Genetics Center, Tarrytown, NY, USA.ORCID http://orcid.org/0000-0003-2975-4108
Aris BarasRegeneron Genetics Center, Tarrytown, NY, USA. aris.baras@regeneron.com.ORCID http://orcid.org/0000-0002-6830-3396
Goncalo R AbecasisRegeneron Genetics Center, Tarrytown, NY, USA. goncalo.abecasis@regeneron.com.ORCID http://orcid.org/0000-0003-1509-1825
Timothy A ThorntonRegeneron Genetics Center, Tarrytown, NY, USA. timothy.thornton@regeneron.com.ORCID http://orcid.org/0000-0001-7071-2642

Funding

Wellcome Trust
6 · The paper itself

Abstract

Whole-genome sequencing (WGS), whole-exome sequencing (WES) and array genotyping with imputation (IMP) are common strategies for assessing genetic variation and its association with medically relevant phenotypes. To date, there has been no systematic empirical assessment of the yield of these approaches when applied to hundreds of thousands of samples to enable the discovery of complex trait genetic signals. Using data for 100 complex traits from 149,195 individuals in the UK Biobank, we systematically compare the relative yield of these strategies in genetic association studies. We find that WGS and WES combined with arrays and imputation (WES + IMP) have the largest association yield. Although WGS results in an approximately fivefold increase in the total number of assayed variants over WES + IMP, the number of detected signals differed by only 1% for both single-variant and gene-based association analyses. Given that WES + IMP typically results in savings of lab and computational time and resources expended per sample, we evaluate the potential benefits of applying WES + IMP to larger samples. When we extend our WES + IMP analyses to 468,169 UK Biobank individuals, we observe an approximately fourfold increase in association signals with the threefold increase in sample size. We conclude that prioritizing WES + IMP and large sample sizes rather than contemporary short-read WGS alternatives will maximize the number of discoveries in genetic association studies.

Indexed as

Biological Specimen BanksExomeExome SequencingGenome, HumanGenome-Wide Association StudyWhole Genome SequencingGenotypeHumansPhenotypePolymorphism, Single NucleotideUK BiobankUnited Kingdom

Identifiers

PMID39322778
PMCPMC11549045

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.