Evidence map›Paper›PMID 26376864›Full record

SynthesisHuman molecular genetics2015

Gene-based meta-analysis of genome-wide association studies implicates new loci involved in obesity.

Sara Hägg, Andrea Ganna, Sander W Van Der Laan, Tonu Esko, Tune H Pers, Adam E Locke, Sonja I Berndt, Anne E Justice, Bratati Kahali, Marten A Siemelink and 9 more

Abstract readMeta-Analysis
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in Human molecular genetics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
37citing papers in PubMed, 3 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

37 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
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  4. Review
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  10. Observational
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  12. Evaluating statistical significance in aComputational and structural biotechnology journal · 2022
    Article
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  20. The Interaction between Genetic Polymorphisms inJournal of personalized medicine · 2019
    Article
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

19 authors.

Sara HäggDepartment of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden, Molecular Epidemiology and Science for Life Laboratory, Department of Medical Sciences, Uppsala University, SE-751 41 Uppsala, Sweden.
Andrea GannaProgram in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA, Analytical and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
Sander W Van Der LaanLaboratory of Experimental Cardiology, Division of Heart and Lungs, University Medical Center Utrecht, Utrecht 3584 CX, The Netherlands.
Tonu EskoDivisions of Endocrinology and Genetics and Center for Basic and Translational Obesity Research, Boston Children's Hospital, Boston, MA 02115, USA, Broad Institute of the Massachusetts Institute of Technology and Harvard University, Cambridge, MA 02142, USA, Department of Genetics, Harvard Medical School, Boston, MA 02115, USA, Estonian Genome Center, University of Tartu, Tartu 51010, Estonia.
Tune H PersDivisions of Endocrinology and Genetics and Center for Basic and Translational Obesity Research, Boston Children's Hospital, Boston, MA 02115, USA, Broad Institute of the Massachusetts Institute of Technology and Harvard University, Cambridge, MA 02142, USA, Department of Genetics, Harvard Medical School, Boston, MA 02115, USA, Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark, Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark.
Adam E LockeCenter for Statistical Genetics, Department of Biostatistics.
Sonja I BerndtDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA.
Anne E JusticeDepartment of Epidemiology.
Bratati KahaliDepartment of Internal Medicine, Division of Gastroenterology, Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA.
Marten A SiemelinkLaboratory of Experimental Cardiology, Division of Heart and Lungs, University Medical Center Utrecht, Utrecht 3584 CX, The Netherlands.
Gerard PasterkampLaboratory of Experimental Cardiology, Division of Heart and Lungs, University Medical Center Utrecht, Utrecht 3584 CX, The Netherlands, Laboratory of Clinical Chemistry and Hematology, Division Laboratories & Pharmacy, UMC Utrecht, Utrecht, The Netherlands.
GIANT Consortium
David P StrachanSt George's, University of London, London SW17 0RE, UK.
Elizabeth K SpeliotesDepartment of Internal Medicine, Division of Gastroenterology, Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA.
Kari E NorthDepartment of Epidemiology, Carolina Center for Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
Ruth J F LoosMRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Addenbrooke's Hospital, Hills Road, Cambridge CB2 0QQ, UK, The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA, The Genetics of Obesity and Related Metabolic Traits Program, The Mindich Child Health and Development Institute.
Joel N HirschhornDivisions of Endocrinology and Genetics and Center for Basic and Translational Obesity Research, Boston Children's Hospital, Boston, MA 02115, USA, Broad Institute of the Massachusetts Institute of Technology and Harvard University, Cambridge, MA 02142, USA, Department of Genetics, Harvard Medical School, Boston, MA 02115, USA.
Yudi PawitanDepartment of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
Erik IngelssonMolecular Epidemiology and Science for Life Laboratory, Department of Medical Sciences, Uppsala University, SE-751 41 Uppsala, Sweden, Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK and Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA erik.ingelsson@medsci.uu.se.

Funding

University of Michigan Center for Gastrointestinal ResearchP30DK034933 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI MERCHANT, JUANITA L. · 1986 to 2021
$22.5M
Cell Interactions in the Inflamed Intestinal MucosaR01DK075787 · NIDDK · BOSTON CHILDREN'S HOSPITAL · PI JOEL N HIRSCHHORN · 2007 to 2026
$13.1M
Cardiovascular Epidemiology Training GrantT32HL007055 · NHLBI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Wayne D. Rosamond · 1986 to 2026
$10.0M
Medical Research Council G1001799Medical Research Council MC_U106179471Medical Research Council MC_UU_12015/1Medical Research Council MR/N01104X/1NHLBI NIH HHS T32 HL007055NIDDK NIH HHS P30 DK034933NIDDK NIH HHS R01 DK075787
6 · The paper itself

Abstract

To date, genome-wide association studies (GWASs) have identified >100 loci with single variants associated with body mass index (BMI). This approach may miss loci with high allelic heterogeneity; therefore, the aim of the present study was to use gene-based meta-analysis to identify regions with high allelic heterogeneity to discover additional obesity susceptibility loci. We included GWAS data from 123 865 individuals of European descent from 46 cohorts in Stage 1 and Metabochip data from additional 103 046 individuals from 43 cohorts in Stage 2, all within the Genetic Investigation of ANthropometric Traits (GIANT) consortium. Each cohort was tested for association between ∼2.4 million (Stage 1) or ∼200 000 (Stage 2) imputed or genotyped single variants and BMI, and summary statistics were subsequently meta-analyzed in 17 941 genes. We used the 'VErsatile Gene-based Association Study' (VEGAS) approach to assign variants to genes and to calculate gene-based P-values based on simulations. The VEGAS method was applied to each cohort separately before a gene-based meta-analysis was performed. In Stage 1, two known (FTO and TMEM18) and six novel (PEX2, MTFR2, SSFA2, IARS2, CEP295 and TXNDC12) loci were associated with BMI (P < 2.8 × 10(-6) for 17 941 gene tests). We confirmed all loci, and six of them were gene-wide significant in Stage 2 alone. We provide biological support for the loci by pathway, expression and methylation analyses. Our results indicate that gene-based meta-analysis of GWAS provides a useful strategy to find loci of interest that were not identified in standard single-marker analyses due to high allelic heterogeneity.

Indexed as

Body Mass IndexGenetic LociGenetic Predisposition to DiseaseFemaleGenome-Wide Association StudyHumansObesityPolymorphism, Single NucleotideWhite People

Identifiers

PMID26376864
PMCPMC4643645

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.