Genetic variants including markers from the exome chip and metabolite traits of type 2 diabetes

Susanne Jäger; Simone Wahl; Janine Kröger; Sapna Sharma; Per Hoffmann; Anna Floegel; Tobias Pischon; Cornelia Prehn; Jerzy Adamski; Martina Müller-Nurasyid; Melanie Waldenberger; Konstantin Strauch; Annette Peters; Christian Gieger; Karsten Suhre; Harald Grallert; Heiner Boeing; Matthias B. Schulze; Karina Meidtner

doi:10.1038/s41598-017-06158-3

Genetic variants including markers from the exome chip and metabolite traits of type 2 diabetes

Susanne Jäger
, Simone Wahl
, Janine Kröger
, Sapna Sharma
, Per Hoffmann
, Anna Floegel
, Tobias Pischon
, Cornelia Prehn
, Jerzy Adamski
, Martina Müller-Nurasyid
, Melanie Waldenberger
, Konstantin Strauch
, Annette Peters
, Christian Gieger
, Karsten Suhre
, Harald Grallert
, Heiner Boeing
, Matthias B. Schulze
, Karina Meidtner

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

13 Scopus citations

Abstract

Diabetes-associated metabolites may aid the identification of new risk variants for type 2 diabetes. Using targeted metabolomics within a subsample of the German EPIC-Potsdam study (n = 2500), we tested previously published SNPs for their association with diabetes-associated metabolites and conducted an additional exploratory analysis using data from the exome chip including replication within 2,692 individuals from the German KORA F4 study. We identified a total of 16 loci associated with diabetes-related metabolite traits, including one novel association between rs499974 (MOGAT2) and a diacyl-phosphatidylcholine ratio (PC aa C40:5/PC aa C38:5). Gene-based tests on all exome chip variants revealed associations between GFRAL and PC aa C42:1/PC aa C42:0, BIN1 and SM (OH) C22:2/SM C18:0 and TFRC and SM (OH) C22:2/SM C16:1). Selecting variants for gene-based tests based on functional annotation identified one additional association between OR51Q1 and hexoses. Among single genetic variants consistently associated with diabetes-related metabolites, two (rs174550 (FADS1), rs3204953 (REV3L)) were significantly associated with type 2 diabetes in large-scale meta-analysis for type 2 diabetes. In conclusion, we identified a novel metabolite locus in single variant analyses and four genes within gene-based tests and confirmed two previously known mGWAS loci which might be relevant for the risk of type 2 diabetes.

Original language	English
Article number	6037
Journal	Scientific Reports
Volume	7
Issue number	1
DOIs	https://doi.org/10.1038/s41598-017-06158-3
State	Published - 1 Dec 2017
Externally published	Yes

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This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

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10.1038/s41598-017-06158-3

Cite this

Jäger, S., Wahl, S., Kröger, J., Sharma, S., Hoffmann, P., Floegel, A., Pischon, T., Prehn, C., Adamski, J., Müller-Nurasyid, M., Waldenberger, M., Strauch, K., Peters, A., Gieger, C., Suhre, K., Grallert, H., Boeing, H., Schulze, M. B., & Meidtner, K. (2017). Genetic variants including markers from the exome chip and metabolite traits of type 2 diabetes. Scientific Reports, 7(1), Article 6037. https://doi.org/10.1038/s41598-017-06158-3

@article{91756e5124ea42ea97f517f7feca364b,

title = "Genetic variants including markers from the exome chip and metabolite traits of type 2 diabetes",

abstract = "Diabetes-associated metabolites may aid the identification of new risk variants for type 2 diabetes. Using targeted metabolomics within a subsample of the German EPIC-Potsdam study (n = 2500), we tested previously published SNPs for their association with diabetes-associated metabolites and conducted an additional exploratory analysis using data from the exome chip including replication within 2,692 individuals from the German KORA F4 study. We identified a total of 16 loci associated with diabetes-related metabolite traits, including one novel association between rs499974 (MOGAT2) and a diacyl-phosphatidylcholine ratio (PC aa C40:5/PC aa C38:5). Gene-based tests on all exome chip variants revealed associations between GFRAL and PC aa C42:1/PC aa C42:0, BIN1 and SM (OH) C22:2/SM C18:0 and TFRC and SM (OH) C22:2/SM C16:1). Selecting variants for gene-based tests based on functional annotation identified one additional association between OR51Q1 and hexoses. Among single genetic variants consistently associated with diabetes-related metabolites, two (rs174550 (FADS1), rs3204953 (REV3L)) were significantly associated with type 2 diabetes in large-scale meta-analysis for type 2 diabetes. In conclusion, we identified a novel metabolite locus in single variant analyses and four genes within gene-based tests and confirmed two previously known mGWAS loci which might be relevant for the risk of type 2 diabetes.",

author = "Susanne J{\"a}ger and Simone Wahl and Janine Kr{\"o}ger and Sapna Sharma and Per Hoffmann and Anna Floegel and Tobias Pischon and Cornelia Prehn and Jerzy Adamski and Martina M{\"u}ller-Nurasyid and Melanie Waldenberger and Konstantin Strauch and Annette Peters and Christian Gieger and Karsten Suhre and Harald Grallert and Heiner Boeing and Schulze, \{Matthias B.\} and Karina Meidtner",

note = "Publisher Copyright: {\textcopyright} 2017 The Author(s).",

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doi = "10.1038/s41598-017-06158-3",

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Jäger, S, Wahl, S, Kröger, J, Sharma, S, Hoffmann, P, Floegel, A, Pischon, T, Prehn, C, Adamski, J, Müller-Nurasyid, M, Waldenberger, M, Strauch, K, Peters, A, Gieger, C, Suhre, K, Grallert, H, Boeing, H, Schulze, MB & Meidtner, K 2017, 'Genetic variants including markers from the exome chip and metabolite traits of type 2 diabetes', Scientific Reports, vol. 7, no. 1, 6037. https://doi.org/10.1038/s41598-017-06158-3

TY - JOUR

T1 - Genetic variants including markers from the exome chip and metabolite traits of type 2 diabetes

AU - Jäger, Susanne

AU - Wahl, Simone

AU - Kröger, Janine

AU - Sharma, Sapna

AU - Hoffmann, Per

AU - Floegel, Anna

AU - Pischon, Tobias

AU - Prehn, Cornelia

AU - Adamski, Jerzy

AU - Müller-Nurasyid, Martina

AU - Waldenberger, Melanie

AU - Strauch, Konstantin

AU - Peters, Annette

AU - Gieger, Christian

AU - Suhre, Karsten

AU - Grallert, Harald

AU - Boeing, Heiner

AU - Schulze, Matthias B.

AU - Meidtner, Karina

PY - 2017/12/1

Y1 - 2017/12/1

N2 - Diabetes-associated metabolites may aid the identification of new risk variants for type 2 diabetes. Using targeted metabolomics within a subsample of the German EPIC-Potsdam study (n = 2500), we tested previously published SNPs for their association with diabetes-associated metabolites and conducted an additional exploratory analysis using data from the exome chip including replication within 2,692 individuals from the German KORA F4 study. We identified a total of 16 loci associated with diabetes-related metabolite traits, including one novel association between rs499974 (MOGAT2) and a diacyl-phosphatidylcholine ratio (PC aa C40:5/PC aa C38:5). Gene-based tests on all exome chip variants revealed associations between GFRAL and PC aa C42:1/PC aa C42:0, BIN1 and SM (OH) C22:2/SM C18:0 and TFRC and SM (OH) C22:2/SM C16:1). Selecting variants for gene-based tests based on functional annotation identified one additional association between OR51Q1 and hexoses. Among single genetic variants consistently associated with diabetes-related metabolites, two (rs174550 (FADS1), rs3204953 (REV3L)) were significantly associated with type 2 diabetes in large-scale meta-analysis for type 2 diabetes. In conclusion, we identified a novel metabolite locus in single variant analyses and four genes within gene-based tests and confirmed two previously known mGWAS loci which might be relevant for the risk of type 2 diabetes.

AB - Diabetes-associated metabolites may aid the identification of new risk variants for type 2 diabetes. Using targeted metabolomics within a subsample of the German EPIC-Potsdam study (n = 2500), we tested previously published SNPs for their association with diabetes-associated metabolites and conducted an additional exploratory analysis using data from the exome chip including replication within 2,692 individuals from the German KORA F4 study. We identified a total of 16 loci associated with diabetes-related metabolite traits, including one novel association between rs499974 (MOGAT2) and a diacyl-phosphatidylcholine ratio (PC aa C40:5/PC aa C38:5). Gene-based tests on all exome chip variants revealed associations between GFRAL and PC aa C42:1/PC aa C42:0, BIN1 and SM (OH) C22:2/SM C18:0 and TFRC and SM (OH) C22:2/SM C16:1). Selecting variants for gene-based tests based on functional annotation identified one additional association between OR51Q1 and hexoses. Among single genetic variants consistently associated with diabetes-related metabolites, two (rs174550 (FADS1), rs3204953 (REV3L)) were significantly associated with type 2 diabetes in large-scale meta-analysis for type 2 diabetes. In conclusion, we identified a novel metabolite locus in single variant analyses and four genes within gene-based tests and confirmed two previously known mGWAS loci which might be relevant for the risk of type 2 diabetes.

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DO - 10.1038/s41598-017-06158-3

M3 - Article

C2 - 28729637

AN - SCOPUS:85025462539

SN - 2045-2322

VL - 7

JO - Scientific Reports

JF - Scientific Reports

IS - 1

M1 - 6037

ER -

Genetic variants including markers from the exome chip and metabolite traits of type 2 diabetes

Abstract

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