Evidence map›Paper›PMID 31704910›Full record

ArticleNature communications2019

Improved polygenic prediction by Bayesian multiple regression on summary statistics.

Luke R Lloyd-Jones, Jian Zeng, Julia Sidorenko, Loïc Yengo, Gerhard Moser, Kathryn E Kemper, Huanwei Wang, Zhili Zheng, Reedik Magi, Tõnu Esko and 5 more

Abstract read
In one paragraph

Article in Nature communications, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 340 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
340citing 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

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

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280 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

15 authors.

Luke R Lloyd-JonesInstitute for Molecular Bioscience, University of Queensland, St Lucia, Brisbane, 4072, QLD, Australia. luke.lloydjones@uqconnect.edu.au.ORCID http://orcid.org/0000-0002-0229-0625
Jian ZengInstitute for Molecular Bioscience, University of Queensland, St Lucia, Brisbane, 4072, QLD, Australia. j.zeng@uq.edu.au.ORCID http://orcid.org/0000-0001-8801-5220
Julia SidorenkoInstitute for Molecular Bioscience, University of Queensland, St Lucia, Brisbane, 4072, QLD, Australia.
Loïc YengoInstitute for Molecular Bioscience, University of Queensland, St Lucia, Brisbane, 4072, QLD, Australia.
Gerhard MoserSchool of Engineering and Technology, Central Queensland University, Rockhampton, 4702, QLD, Australia.
Kathryn E KemperInstitute for Molecular Bioscience, University of Queensland, St Lucia, Brisbane, 4072, QLD, Australia.
Huanwei WangInstitute for Molecular Bioscience, University of Queensland, St Lucia, Brisbane, 4072, QLD, Australia.ORCID http://orcid.org/0000-0002-6137-3391
Zhili ZhengInstitute for Molecular Bioscience, University of Queensland, St Lucia, Brisbane, 4072, QLD, Australia.
Reedik MagiEstonian Genome Center, Institute of Genomics, University of Tartu, Riia 23b, 51010, Tartu, Estonia.
Tõnu EskoEstonian Genome Center, Institute of Genomics, University of Tartu, Riia 23b, 51010, Tartu, Estonia.
Andres MetspaluEstonian Genome Center, Institute of Genomics, University of Tartu, Riia 23b, 51010, Tartu, Estonia.
Naomi R WrayInstitute for Molecular Bioscience, University of Queensland, St Lucia, Brisbane, 4072, QLD, Australia.ORCID http://orcid.org/0000-0001-7421-3357
Michael E GoddardFaculty of Veterinary and Agricultural Science, University of Melbourne, Melbourne, 3052, VIC, Australia.
Jian YangInstitute for Molecular Bioscience, University of Queensland, St Lucia, Brisbane, 4072, QLD, Australia. jian.yang.qt@gmail.com.ORCID http://orcid.org/0000-0003-2001-2474
Peter M VisscherInstitute for Molecular Bioscience, University of Queensland, St Lucia, Brisbane, 4072, QLD, Australia. peter.visscher@uq.edu.au.ORCID http://orcid.org/0000-0002-2143-8760

Funding

Estimating the genetic and environmental architecture of psychiatric disordersR01MH100141 · NIMH · UNIVERSITY OF COLORADO · PI KELLER, MATTHEW CHARLES · 2013 to 2022
$5.3M
Genome-Wide Analyses of Health and Well-Being PhenotypesR01AG042568 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI BENJAMIN, DANIEL J · 2015 to 2021
$2.8M
Genome-Wide Analyses of Health and Well-Being PhenotypesR56AG042568 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI BENJAMIN, DANIEL J · 2018 to 2018
$803k
Increasing the power of GxE detection by using multi-locus genome-wide predictorsR21ES025052 · NIEHS · HARVARD MEDICAL SCHOOL · PI PATEL, CHIRAG J. · 2015 to 2017
$434k
Medical Research Council MC_PC_17228Medical Research Council MC_QA137853NIA NIH HHS R01 AG042568NIA NIH HHS R56 AG042568NIEHS NIH HHS R21 ES025052NIMH NIH HHS R01 MH100141
6 · The paper itself

Abstract

Accurate prediction of an individual's phenotype from their DNA sequence is one of the great promises of genomics and precision medicine. We extend a powerful individual-level data Bayesian multiple regression model (BayesR) to one that utilises summary statistics from genome-wide association studies (GWAS), SBayesR. In simulation and cross-validation using 12 real traits and 1.1 million variants on 350,000 individuals from the UK Biobank, SBayesR improves prediction accuracy relative to commonly used state-of-the-art summary statistics methods at a fraction of the computational resources. Furthermore, using summary statistics for variants from the largest GWAS meta-analysis (n ≈ 700, 000) on height and BMI, we show that on average across traits and two independent data sets that SBayesR improves prediction R

Indexed as

Bayes TheoremRegression AnalysisAdipose TissueAlopeciaBasal MetabolismBiological Specimen BanksBirth WeightBody CompositionBody HeightBody Mass IndexBone DensityDiabetes Mellitus, Type 2Forced Expiratory VolumeGenetic Association StudiesGenome-Wide Association StudyHumans

Identifiers

PMID31704910
PMCPMC6841727

What OpenQuestion holds

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Registered trials

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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.