Heritability estimates for 361 blood metabolites across 40 genome-wide association studies

Fiona A. Hagenbeek; Rene Pool; Jenny van Dongen; Harmen H. M. Draisma; Jouke Jan Hottenga; Gonneke Willemsen; Abdel Abdellaoui; Iryna O. Fedko; Anouk den Braber; Pieter Jelle Visser; Eco J. C. N. de Geus; Ko Willems van Dijk; Aswin Verhoeven; H. Eka Suchiman; Marian Beekman; P. Eline Slagboom; Cornelia M. van Duijn; Amy C. Harms; Thomas Hankemeier; Meike Bartels; Michel G. Nivard; Dorret I. Boomsma; J. J. H. Barkey Wolf; D. Cats; N. Amin; J. W. Beulens; J. A. van der Bom; N. Bomer; A. Demirkan; J. A. van Hilten; J. M. T. A. Meessen; M. H. Moed; J. Fu; G. L. J. Onderwater; F. Rutters; C. So-Osman; W. M. van der Flier; A. A. W. A. van der Heijden; A. van der Spek; F. W. Asselbergs; E. Boersma; P. M. Elders; J. M. Geleijnse; R. G. H. H. Nelissen; C. D. A. Stehouwer; C. E. Teunissen; I. C. C. van der Horst; C. J. H. van der Kallen; M. M. J. van Greevenbroek; M. J. T. Reinders; BBMRI Metabolomics Consortium

doi:10.1038/s41467-019-13770-6

Heritability estimates for 361 blood metabolites across 40 genome-wide association studies

Fiona A. Hagenbeek^*, Rene Pool, Jenny van Dongen, Harmen H. M. Draisma, Jouke Jan Hottenga, Gonneke Willemsen, Abdel Abdellaoui, Iryna O. Fedko, Anouk den Braber, Pieter Jelle Visser, Eco J. C. N. de Geus, Ko Willems van Dijk, Aswin Verhoeven, H. Eka Suchiman, Marian Beekman, P. Eline Slagboom, Cornelia M. van Duijn, Amy C. Harms, Thomas Hankemeier, Meike BartelsMichel G. Nivard^*, Dorret I. Boomsma^*, J. J. H. Barkey Wolf, D. Cats, N. Amin, J. W. Beulens, J. A. van der Bom, N. Bomer, A. Demirkan, J. A. van Hilten, J. M. T. A. Meessen, M. H. Moed, J. Fu, G. L. J. Onderwater, F. Rutters, C. So-Osman, W. M. van der Flier, A. A. W. A. van der Heijden, A. van der Spek, F. W. Asselbergs, E. Boersma, P. M. Elders, J. M. Geleijnse, R. G. H. H. Nelissen, C. D. A. Stehouwer, C. E. Teunissen, I. C. C. van der Horst, C. J. H. van der Kallen, M. M. J. van Greevenbroek, M. J. T. Reinders, BBMRI Metabolomics Consortium

^*Corresponding author for this work

Research output: Contribution to journal › Article › Academic › peer-review

27 Citations (Web of Science)

Abstract

Metabolomics examines the small molecules involved in cellular metabolism. Approximately 50% of total phenotypic differences in metabolite levels is due to genetic variance, but heritability estimates differ across metabolite classes. We perform a review of all genome-wide association and (exome-) sequencing studies published between November 2008 and October 2018, and identify > 800 class-specific metabolite loci associated with metabolite levels. In a twin-family cohort (N = 5117), these metabolite loci are leveraged to simultaneously estimate total heritability (h(total)(2)), and the proportion of heritability captured by known metabolite loci (h(Metabolite-hits)(2)) for 309 lipids and 52 organic acids. Our study reveals significant differences in h(Metabolite-hits)(2) among different classes of lipids and organic acids. Furthermore, phosphatidylcholines with a high degree of unsaturation have higher h(Metabolite-hits)(2) estimates than phosphatidylcholines with low degrees of unsaturation. This study highlights the importance of common genetic variants for metabolite levels, and elucidates the genetic architecture of metabolite classes.

Original language	English
Article number	39
Number of pages	11
Journal	Nature Communications
Volume	11
Issue number	1
DOIs	https://doi.org/10.1038/s41467-019-13770-6
Publication status	Published - 7 Jan 2020

Keywords

NETHERLANDS TWIN REGISTER
MISSING HERITABILITY
GENOTYPE IMPUTATION
VARIANCE-ESTIMATION
METABOLOMICS
SELECTION
DATABASE
BIOBANK

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10.1038/s41467-019-13770-6

27 Citations
1 Erratum / corrigendum / retractions

Author Correction: Heritability estimates for 361 blood metabolites across 40 genome-wide association studies
Stehouwer, C., van der Kallen, C., van Greevenbroek, M. & BBMRI Metabolomics Consortium, 31 Mar 2020, In: Nature Communications. 11, 1, 1 p., 1702.
Research output: Contribution to journal › Erratum / corrigendum / retractions › Academic

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Hagenbeek, F. A., Pool, R., van Dongen, J., Draisma, H. H. M., Jan Hottenga, J., Willemsen, G., Abdellaoui, A., Fedko, I. O., den Braber, A., Visser, P. J., de Geus, E. J. C. N., Willems van Dijk, K., Verhoeven, A., Suchiman, H. E., Beekman, M., Slagboom, P. E., van Duijn, C. M., Harms, A. C., Hankemeier, T., ... BBMRI Metabolomics Consortium (2020). Heritability estimates for 361 blood metabolites across 40 genome-wide association studies. Nature Communications, 11(1), [39]. https://doi.org/10.1038/s41467-019-13770-6

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title = "Heritability estimates for 361 blood metabolites across 40 genome-wide association studies",

abstract = "Metabolomics examines the small molecules involved in cellular metabolism. Approximately 50% of total phenotypic differences in metabolite levels is due to genetic variance, but heritability estimates differ across metabolite classes. We perform a review of all genome-wide association and (exome-) sequencing studies published between November 2008 and October 2018, and identify > 800 class-specific metabolite loci associated with metabolite levels. In a twin-family cohort (N = 5117), these metabolite loci are leveraged to simultaneously estimate total heritability (h(total)(2)), and the proportion of heritability captured by known metabolite loci (h(Metabolite-hits)(2)) for 309 lipids and 52 organic acids. Our study reveals significant differences in h(Metabolite-hits)(2) among different classes of lipids and organic acids. Furthermore, phosphatidylcholines with a high degree of unsaturation have higher h(Metabolite-hits)(2) estimates than phosphatidylcholines with low degrees of unsaturation. This study highlights the importance of common genetic variants for metabolite levels, and elucidates the genetic architecture of metabolite classes.",

keywords = "NETHERLANDS TWIN REGISTER, MISSING HERITABILITY, GENOTYPE IMPUTATION, VARIANCE-ESTIMATION, METABOLOMICS, SELECTION, DATABASE, BIOBANK",

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Hagenbeek, FA, Pool, R, van Dongen, J, Draisma, HHM, Jan Hottenga, J, Willemsen, G, Abdellaoui, A, Fedko, IO, den Braber, A, Visser, PJ, de Geus, EJCN, Willems van Dijk, K, Verhoeven, A, Suchiman, HE, Beekman, M, Slagboom, PE, van Duijn, CM, Harms, AC, Hankemeier, T, Bartels, M, Nivard, MG, Boomsma, DI, Wolf, JJHB, Cats, D, Amin, N, Beulens, JW, van der Bom, JA, Bomer, N, Demirkan, A, van Hilten, JA, Meessen, JMTA, Moed, MH, Fu, J, Onderwater, GLJ, Rutters, F, So-Osman, C, van der Flier, WM, van der Heijden, AAWA, van der Spek, A, Asselbergs, FW, Boersma, E, Elders, PM, Geleijnse, JM, Nelissen, RGHH, Stehouwer, CDA, Teunissen, CE, van der Horst, ICC , van der Kallen, CJH , van Greevenbroek, MMJ, Reinders, MJT & BBMRI Metabolomics Consortium 2020, 'Heritability estimates for 361 blood metabolites across 40 genome-wide association studies', Nature Communications, vol. 11, no. 1, 39. https://doi.org/10.1038/s41467-019-13770-6

TY - JOUR

T1 - Heritability estimates for 361 blood metabolites across 40 genome-wide association studies

AU - Hagenbeek, Fiona A.

AU - Pool, Rene

AU - van Dongen, Jenny

AU - Draisma, Harmen H. M.

AU - Jan Hottenga, Jouke

AU - Willemsen, Gonneke

AU - Abdellaoui, Abdel

AU - Fedko, Iryna O.

AU - den Braber, Anouk

AU - Visser, Pieter Jelle

AU - de Geus, Eco J. C. N.

AU - Willems van Dijk, Ko

AU - Verhoeven, Aswin

AU - Suchiman, H. Eka

AU - Beekman, Marian

AU - Slagboom, P. Eline

AU - van Duijn, Cornelia M.

AU - Harms, Amy C.

AU - Hankemeier, Thomas

AU - Bartels, Meike

AU - Nivard, Michel G.

AU - Boomsma, Dorret I.

AU - Wolf, J. J. H. Barkey

AU - Cats, D.

AU - Amin, N.

AU - Beulens, J. W.

AU - van der Bom, J. A.

AU - Bomer, N.

AU - Demirkan, A.

AU - van Hilten, J. A.

AU - Meessen, J. M. T. A.

AU - Moed, M. H.

AU - Fu, J.

AU - Onderwater, G. L. J.

AU - Rutters, F.

AU - So-Osman, C.

AU - van der Flier, W. M.

AU - van der Heijden, A. A. W. A.

AU - van der Spek, A.

AU - Asselbergs, F. W.

AU - Boersma, E.

AU - Elders, P. M.

AU - Geleijnse, J. M.

AU - Nelissen, R. G. H. H.

AU - Stehouwer, C. D. A.

AU - Teunissen, C. E.

AU - van der Horst, I. C. C.

AU - van der Kallen, C. J. H.

AU - van Greevenbroek, M. M. J.

AU - Reinders, M. J. T.

AU - BBMRI Metabolomics Consortium

PY - 2020/1/7

Y1 - 2020/1/7

N2 - Metabolomics examines the small molecules involved in cellular metabolism. Approximately 50% of total phenotypic differences in metabolite levels is due to genetic variance, but heritability estimates differ across metabolite classes. We perform a review of all genome-wide association and (exome-) sequencing studies published between November 2008 and October 2018, and identify > 800 class-specific metabolite loci associated with metabolite levels. In a twin-family cohort (N = 5117), these metabolite loci are leveraged to simultaneously estimate total heritability (h(total)(2)), and the proportion of heritability captured by known metabolite loci (h(Metabolite-hits)(2)) for 309 lipids and 52 organic acids. Our study reveals significant differences in h(Metabolite-hits)(2) among different classes of lipids and organic acids. Furthermore, phosphatidylcholines with a high degree of unsaturation have higher h(Metabolite-hits)(2) estimates than phosphatidylcholines with low degrees of unsaturation. This study highlights the importance of common genetic variants for metabolite levels, and elucidates the genetic architecture of metabolite classes.

AB - Metabolomics examines the small molecules involved in cellular metabolism. Approximately 50% of total phenotypic differences in metabolite levels is due to genetic variance, but heritability estimates differ across metabolite classes. We perform a review of all genome-wide association and (exome-) sequencing studies published between November 2008 and October 2018, and identify > 800 class-specific metabolite loci associated with metabolite levels. In a twin-family cohort (N = 5117), these metabolite loci are leveraged to simultaneously estimate total heritability (h(total)(2)), and the proportion of heritability captured by known metabolite loci (h(Metabolite-hits)(2)) for 309 lipids and 52 organic acids. Our study reveals significant differences in h(Metabolite-hits)(2) among different classes of lipids and organic acids. Furthermore, phosphatidylcholines with a high degree of unsaturation have higher h(Metabolite-hits)(2) estimates than phosphatidylcholines with low degrees of unsaturation. This study highlights the importance of common genetic variants for metabolite levels, and elucidates the genetic architecture of metabolite classes.

KW - NETHERLANDS TWIN REGISTER

KW - MISSING HERITABILITY

KW - GENOTYPE IMPUTATION

KW - VARIANCE-ESTIMATION

KW - METABOLOMICS

KW - SELECTION

KW - DATABASE

KW - BIOBANK

U2 - 10.1038/s41467-019-13770-6

DO - 10.1038/s41467-019-13770-6

M3 - Article

C2 - 31911595

VL - 11

JO - Nature Communications

JF - Nature Communications

SN - 2041-1723

IS - 1

M1 - 39

ER -

Heritability estimates for 361 blood metabolites across 40 genome-wide association studies

Abstract

Keywords

Access to Document

Research output

Author Correction: Heritability estimates for 361 blood metabolites across 40 genome-wide association studies

Cite this