SynthesisNature communications2015
Genome-wide association study identifies novel genetic variants contributing to variation in blood metabolite levels.
Open access · goldAbstract readMeta-Analysis
In one paragraph
Synthesis in Nature communications, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 118 papers, 8 of them syntheses that pooled it.
0numbers the graph read from it
0cells of the map it votes in
118citing papers in PubMed, 8 pooled it
15.6field-weighted citation impact, top 1% of its field
What it found
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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.
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.
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Who cites it
118 citing papers in PubMed, 8 syntheses or guidelines pooled it, 221 citations in OpenAlex.
- Use of Mendelian Randomization to Unveil Metabolic Markers inJournal of Korean medical science · 2026Pooled it
- Cross-ancestry analyses of Chinese and European populations reveal insights into the genetic architecture and disease implication of metabolites.Cell genomics · 2025Pooled it
- Multiomic integration analysis identifies atherogenic metabolites mediating between novel immune genes and cardiovascular risk.Genome medicine · 2024Pooled it
- Comprehensive genetic analysis of the human lipidome identifies loci associated with lipid homeostasis with links to coronary artery disease.Nature communications · 2022Pooled it
- Genetic Determinants of Circulating Glycine Levels and Risk of Coronary Artery Disease.Journal of the American Heart Association · 2019Pooled it
- Assessing the causal association of glycine with risk of cardio-metabolic diseases.Nature communications · 2019Pooled it
- Integrative genomic analysis predicts novel functional enhancer-SNPs for bone mineral density.Human genetics · 2019Pooled it
- Genome-wide association study of 23,500 individuals identifies 7 loci associated with brain ventricular volume.Nature communications · 2018Pooled it
- Association of Physical Activity With Bioactive Lipids and Cardiovascular Events.Circulation research · 2022Trial
- Metabolic GWAS of elite athletes reveals novel genetically-influenced metabolites associated with athletic performance.Scientific reports · 2019Trial
- Mendelian-Randomization Study Reveals Causal Relationships Between Blood Metabolites and Psychiatric Disorders.Schizophrenia bulletin · 2026Article
- Technology-enabled insights into SLC transporters in MAFLD: redefining the multi-hit pathogenesis and therapeutic landscape.Acta pharmacologica Sinica · 2026Review
- Population-based genome-wide association study of plasma complex lipid species.Nature communications · 2026Article
- Blood biomarkers and breed genetics of aging in pet dogs.bioRxiv : the preprint server for biology · 2026Article
- Hypothesis-free evaluation of circulating metabolome provides cell-specific insights regarding the role of energy substrate availability in amyotrophic lateral sclerosis.BMC medicine · 2026Article
- Integration of metabolomic and genetic data reveals novel variants underpinning the human metabolome: the Coronary Artery Risk Development in Young Adults (CARDIA) study.medRxiv : the preprint server for health sciences · 2026Article
- HUBMet: an integrative database and analytical platform for human blood metabolites and metabolite-protein associations.Genome biology · 2025Article
- Application of Mendelian randomization to explore metabolic pathways in colorectal cancer.Annals of medicine and surgery (2012) · 2025Article
- Transforming beef quality through healthy breeding: a strategy to reduce carcinogenic compounds and enhance human health: a review.Mammalian genome : official journal of the International Mammalian Genome Society · 2025Review
- Rationale and design of the Dog Aging Project precision cohort: a multi-omic resource for longitudinal research in geroscience.GeroScience · 2025Article
58 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
48 authors at 14 institutions in 8 countries.
Harmen H M Draisma *Department of Biological Psychology, VU University Amsterdam, van der Boechorststraat 1, Amsterdam 1081 BT, The Netherlands.
René Pool *Department of Biological Psychology, VU University Amsterdam, van der Boechorststraat 1, Amsterdam 1081 BT, The Netherlands.
Michael KoblInstitute of Genetic Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Ingolstädter Landstraße 1, Neuherberg 85764, Germany.
Rick JansenDepartment of Psychiatry, VU University Medical Center, Neuroscience Campus Amsterdam, VUmc, A.J. Ernststraat 1187, Amsterdam 1081 HL, The Netherlands.
Ann-Kristin PetersenInstitute of Genetic Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Ingolstädter Landstraße 1, Neuherberg 85764, Germany.
Anika A M VaarhorstBBMRINL: Infrastructure for the Application of Metabolomics Technology in Epidemiology (RP4), S4-P, Postbus 9600, Leiden 2300 RC, The Netherlands.
Idil YetDepartment of Twin Research and Genetic Epidemiology, King's College London, Westminster Bridge Road, London SE1 7EH, UK.
Toomas HallerEstonian Genome Center, University of Tartu, 23b Riia Street, Tartu 51010, Estonia.
Ayşe DemirkanDepartment of Human Genetics, Leiden University Medical Center, S4-P, PO Box 9600, Leiden 2300 RC, The Netherlands.
Tõnu EskoEstonian Genome Center, University of Tartu, 23b Riia Street, Tartu 51010, Estonia.
Gu ZhuDepartment of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, 300 Herston Road, Brisbane 4006, Australia.
Stefan BöhringerDepartment of Medical Statistics and Bioinformatics, Leiden University Medical Center, PO Box 9600, Leiden 2300 RC, The Netherlands.
Marian BeekmanDepartment of Molecular Epidemiology, Leiden University Medical Center, PO Box 9600, Leiden 2300 RC, The Netherlands.
Jan Bert van KlinkenDepartment of Human Genetics, Leiden University Medical Center, S4-P, PO Box 9600, Leiden 2300 RC, The Netherlands.
Werner Römisch-MarglInstitute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, Ingolstädter Landstraße 1, Neuherberg 85764, Germany.
Cornelia PrehnInstitute of Experimental Genetics, Genome Analysis Center, Helmholtz Zentrum München, Ingolstädter Landstraße1, Neuherberg 85764, Germany.
Jerzy AdamskiInstitute of Experimental Genetics, Genome Analysis Center, Helmholtz Zentrum München, Ingolstädter Landstraße1, Neuherberg 85764, Germany.
Anton J M de CraenDepartment of Gerontology and Geriatrics, Leiden University Medical Center, PO Box 9600, Leiden 2300 RC, The Netherlands.
Elisabeth M van LeeuwenGenetic Epidemiology Unit, Department of Epidemiology, Erasmus Medical Center, P.O. Box 2040, Rotterdam 3000 CA, The Netherlands.
Najaf AminGenetic Epidemiology Unit, Department of Epidemiology, Erasmus Medical Center, P.O. Box 2040, Rotterdam 3000 CA, The Netherlands.
Harish DharuriDepartment of Human Genetics, Leiden University Medical Center, S4-P, PO Box 9600, Leiden 2300 RC, The Netherlands.
Harm-Jan WestraDepartment of Genetics, CB50, UniversityMedical Center Groningen, University of Groningen, P.O. Box 30001, Groningen 9700 RB, The Netherlands.
Lude FrankeDepartment of Genetics, CB50, UniversityMedical Center Groningen, University of Groningen, P.O. Box 30001, Groningen 9700 RB, The Netherlands.
Eco J C de GeusDepartment of Biological Psychology, VU University Amsterdam, van der Boechorststraat 1, Amsterdam 1081 BT, The Netherlands.
Jouke Jan HottengaDepartment of Biological Psychology, VU University Amsterdam, van der Boechorststraat 1, Amsterdam 1081 BT, The Netherlands.
Gonneke WillemsenDepartment of Biological Psychology, VU University Amsterdam, van der Boechorststraat 1, Amsterdam 1081 BT, The Netherlands.
Anjali K HendersDepartment of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, 300 Herston Road, Brisbane 4006, Australia.
Grant W MontgomeryDepartment of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, 300 Herston Road, Brisbane 4006, Australia.
Dale R NyholtDepartment of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, 300 Herston Road, Brisbane 4006, Australia.
John B WhitfieldDepartment of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, 300 Herston Road, Brisbane 4006, Australia.
Brenda W PenninxThe EMGO+ Institute for Health and Care Research, VU University Medical Center, Van der Boechorststraat 7, Amsterdam 1081 BT, The Netherlands.
Tim D SpectorDepartment of Twin Research and Genetic Epidemiology, King's College London, Westminster Bridge Road, London SE1 7EH, UK.
Andres MetspaluEstonian Genome Center, University of Tartu, 23b Riia Street, Tartu 51010, Estonia.
P Eline SlagboomBBMRINL: Infrastructure for the Application of Metabolomics Technology in Epidemiology (RP4), S4-P, Postbus 9600, Leiden 2300 RC, The Netherlands.
Ko Willems van DijkDepartment of Human Genetics, Leiden University Medical Center, S4-P, PO Box 9600, Leiden 2300 RC, The Netherlands.
Peter A C 't HoenDepartment of Human Genetics, Leiden University Medical Center, S4-P, PO Box 9600, Leiden 2300 RC, The Netherlands.
Konstantin StrauchInstitute of Genetic Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Ingolstädter Landstraße 1, Neuherberg 85764, Germany.
Nicholas G MartinDepartment of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, 300 Herston Road, Brisbane 4006, Australia.
Gert-Jan B van OmmenDepartment of Human Genetics, Leiden University Medical Center, S4-P, PO Box 9600, Leiden 2300 RC, The Netherlands.
Thomas IlligResearch Unit of Molecular Epidemiology, Helmholtz Zentrum München, Ingolstädter Landstraße 1, Neuherberg 85764, Germany.
Jordana T BellDepartment of Twin Research and Genetic Epidemiology, King's College London, Westminster Bridge Road, London SE1 7EH, UK.
Massimo ManginoDepartment of Twin Research and Genetic Epidemiology, King's College London, Westminster Bridge Road, London SE1 7EH, UK.
Karsten SuhreInstitute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, Ingolstädter Landstraße 1, Neuherberg 85764, Germany.
Mark I McCarthyWellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford OX3 7BN, UK.
Christian GiegerInstitute of Genetic Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Ingolstädter Landstraße 1, Neuherberg 85764, Germany.
Aaron IsaacsGenetic Epidemiology Unit, Department of Epidemiology, Erasmus Medical Center, P.O. Box 2040, Rotterdam 3000 CA, The Netherlands.
Cornelia M van DuijnBBMRINL: Infrastructure for the Application of Metabolomics Technology in Epidemiology (RP4), S4-P, Postbus 9600, Leiden 2300 RC, The Netherlands.
Dorret I BoomsmaDepartment of Biological Psychology, VU University Amsterdam, van der Boechorststraat 1, Amsterdam 1081 BT, The Netherlands.
Leiden University Medical Center · NLHelmholtz Zentrum München · DEAcademic Center for Dentistry Amsterdam · NLQIMR Berghofer Medical Research Institute · AUKing's College London · GBErasmus MC · NLEstonian Biocentre · EEUniversity Medical Center Groningen · NLAmsterdam Neuroscience · NLAmsterdam Public Health · NLBroad Institute · USCentre for Human Genetics · GBQueensland University of Technology · AUZimmer Biomet (Netherlands) · NL
Funding
Cell Interactions in the Inflamed Intestinal MucosaR01DK075787 · NIDDK · BOSTON CHILDREN'S HOSPITAL · PI JOEL N HIRSCHHORN · 2007 to 2026
$13.1MEuropean Research Council 230374NIDDK NIH HHS R01 DK075787NIDDK NIH HHS R01DK075787
Abstract
Metabolites are small molecules involved in cellular metabolism, which can be detected in biological samples using metabolomic techniques. Here we present the results of genome-wide association and meta-analyses for variation in the blood serum levels of 129 metabolites as measured by the Biocrates metabolomic platform. In a discovery sample of 7,478 individuals of European descent, we find 4,068 genome- and metabolome-wide significant (Z-test, P < 1.09 × 10(-9)) associations between single-nucleotide polymorphisms (SNPs) and metabolites, involving 59 independent SNPs and 85 metabolites. Five of the fifty-nine independent SNPs are new for serum metabolite levels, and were followed-up for replication in an independent sample (N = 1,182). The novel SNPs are located in or near genes encoding metabolite transporter proteins or enzymes (SLC22A16, ARG1, AGPS and ACSL1) that have demonstrated biomedical or pharmaceutical importance. The further characterization of genetic influences on metabolic phenotypes is important for progress in biological and medical research.
Indexed as
Genome-Wide Association StudyPolymorphism, Single NucleotideBloodHumans
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