Evidence map›Paper›PMID 26854917›Full record

ArticleNature genetics2016

Integrative approaches for large-scale transcriptome-wide association studies.

Alexander Gusev, Arthur Ko, Huwenbo Shi, Gaurav Bhatia, Wonil Chung, Brenda W J H Penninx, Rick Jansen, Eco J C de Geus, Dorret I Boomsma, Fred A Wright and 15 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Nature genetics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1,652 papers, 13 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1,652citing papers in PubMed, 13 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

1,652 citing papers in PubMed, 13 syntheses or guidelines pooled it.

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  20. Big data and psychiatry: advances, constraints and future directions.World psychiatry : official journal of the World Psychiatric Association (WPA) · 2026
    Article

1,592 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

25 authors.

Alexander GusevDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.
Arthur KoDepartment of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA.ORCID http://orcid.org/0000-0002-1523-7225
Huwenbo ShiBioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, California, USA.
Gaurav BhatiaDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.
Wonil ChungDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.ORCID http://orcid.org/0000-0002-5766-6247
Brenda W J H PenninxDepartment of Psychiatry, VU University Medical Center, Amsterdam, the Netherlands.
Rick JansenDepartment of Psychiatry, VU University Medical Center, Amsterdam, the Netherlands.ORCID http://orcid.org/0000-0002-3333-6737
Eco J C de GeusDepartment of Biological Psychology, VU University, Amsterdam, the Netherlands.ORCID http://orcid.org/0000-0001-6022-2666
Dorret I BoomsmaDepartment of Biological Psychology, VU University, Amsterdam, the Netherlands.
Fred A WrightBioinformatics Research Center, Department of Statistics, Department of Biological Sciences, North Carolina State University, Raleigh, North Carolina, USA.
Patrick F SullivanDepartment of Genetics, University of North Carolina, Chapel Hill, North Carolina, USA.
Elina NikkolaDepartment of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA.
Marcus AlvarezDepartment of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA.
Mete CivelekDepartment of Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA.
Aldons J LusisDepartment of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA.
Terho LehtimäkiDepartment of Clinical Chemistry, Fimlab Laboratories and University of Tampere School of Medicine, Tampere, Finland.
Emma RaitoharjuDepartment of Clinical Chemistry, Fimlab Laboratories and University of Tampere School of Medicine, Tampere, Finland.
Mika KähönenDepartment of Clinical Physiology, Pirkanmaa Hospital District and University of Tampere School of Medicine, Tampere, Finland.
Ilkka SeppäläDepartment of Clinical Chemistry, Fimlab Laboratories and University of Tampere School of Medicine, Tampere, Finland.
Olli T RaitakariResearch Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland.
Johanna KuusistoDepartment of Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland.
Markku LaaksoDepartment of Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland.
Alkes L PriceDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.
Päivi PajukantaDepartment of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA.
Bogdan PasaniucDepartment of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA.

Funding

Systems genomics of metabolic syndrome traitsP01HL028481 · NHLBI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI LUSIS, ALDONS JAKE · 1985 to 2019
$50.2M
UCLA MSD ProgramR25GM055052 · NIGMS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI BARBER, PAUL HENRY, HASSON, TAMA W. · 1996 to 2021
$9.2M
Training Grant in Genomic Analysis and InterpretationT32HG002536 · NHGRI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Valerie A Arboleda, Harold Pimentel · 2002 to 2026
$8.6M
Genomics of dyslipidemia in MexicansR01HL095056 · NHLBI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI PAJUKANTA, PAIVI · 2009 to 2018
$5.9M
Improving Polygenic Prediction using Next-Generation Data SetsR01GM105857 · NIGMS · BRIGHAM AND WOMEN'S HOSPITAL · PI SUNYAEV, SHAMIL · 2014 to 2017
$2.0M
Fine-mapping heritability at known disease loci with correlated markersF32GM106584 · NIGMS · HARVARD SCHOOL OF PUBLIC HEALTH · PI GUSEV, ALEXANDER · 2013 to 2015
$159k
Identification of lipid biomarkers via integrative genomic approaches in Hispanic populationsF31HL127921 · NHLBI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI KO, ARTHUR · 2016 to 2018
$82k
NHGRI NIH HHS T32 HG002536NHGRI NIH HHS T32HG002536NHLBI NIH HHS F31 HL127921NHLBI NIH HHS HL-095056NHLBI NIH HHS HL-28481NHLBI NIH HHS P01 HL028481NHLBI NIH HHS R01 HL095056NIGMS NIH HHS F32 GM106584NIGMS NIH HHS R01 GM053725NIGMS NIH HHS R01 GM105857NIGMS NIH HHS R25 GM055052
6 · The paper itself

Abstract

Many genetic variants influence complex traits by modulating gene expression, thus altering the abundance of one or multiple proteins. Here we introduce a powerful strategy that integrates gene expression measurements with summary association statistics from large-scale genome-wide association studies (GWAS) to identify genes whose cis-regulated expression is associated with complex traits. We leverage expression imputation from genetic data to perform a transcriptome-wide association study (TWAS) to identify significant expression-trait associations. We applied our approaches to expression data from blood and adipose tissue measured in ∼ 3,000 individuals overall. We imputed gene expression into GWAS data from over 900,000 phenotype measurements to identify 69 new genes significantly associated with obesity-related traits (BMI, lipids and height). Many of these genes are associated with relevant phenotypes in the Hybrid Mouse Diversity Panel. Our results showcase the power of integrating genotype, gene expression and phenotype to gain insights into the genetic basis of complex traits.

Indexed as

AnimalsGene Expression RegulationGenetic Predisposition to DiseaseGenome-Wide Association StudyGenotypeHumansMiceObesityPhenotypeQuantitative Trait LociTranscriptome

Identifiers

PMID26854917
PMCPMC4767558

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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.