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Novel biomarkers for pre-diabetes identified by metabolomics.

Wang-Sattler R, Yu Z, Herder C, Messias AC, Floegel A, He Y, Heim K, Campillos M, Holzapfel C, Thorand B, Grallert H, Xu T, Bader E, Huth C, Mittelstrass K, Döring A, Meisinger C, Gieger C, Prehn C, Roemisch-Margl W, Carstensen M, Xie L, Yamanaka-Okumura H, Xing G, Ceglarek U, Thiery J, Giani G, Lickert H, Lin X, Li Y, Boeing H, Joost HG, de Angelis MH, Rathmann W, Suhre K, Prokisch H, Peters A, Meitinger T, Roden M, Wichmann HE, Pischon T, Adamski J, Illig T - Mol. Syst. Biol. (2012)

Bottom Line: We identified three metabolites (glycine, lysophosphatidylcholine (LPC) (18:2) and acetylcarnitine) that had significantly altered levels in IGT individuals as compared to those with normal glucose tolerance, with P-values ranging from 2.4×10(-4) to 2.1×10(-13).Lower levels of glycine and LPC were found to be predictors not only for IGT but also for T2D, and were independently confirmed in the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam cohort.Our results may help developing novel strategies to prevent T2D.

View Article: PubMed Central - PubMed

Affiliation: Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany. rui.wang-sattler@helmholtz-muenchen.de

ABSTRACT
Type 2 diabetes (T2D) can be prevented in pre-diabetic individuals with impaired glucose tolerance (IGT). Here, we have used a metabolomics approach to identify candidate biomarkers of pre-diabetes. We quantified 140 metabolites for 4297 fasting serum samples in the population-based Cooperative Health Research in the Region of Augsburg (KORA) cohort. Our study revealed significant metabolic variation in pre-diabetic individuals that are distinct from known diabetes risk indicators, such as glycosylated hemoglobin levels, fasting glucose and insulin. We identified three metabolites (glycine, lysophosphatidylcholine (LPC) (18:2) and acetylcarnitine) that had significantly altered levels in IGT individuals as compared to those with normal glucose tolerance, with P-values ranging from 2.4×10(-4) to 2.1×10(-13). Lower levels of glycine and LPC were found to be predictors not only for IGT but also for T2D, and were independently confirmed in the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam cohort. Using metabolite-protein network analysis, we identified seven T2D-related genes that are associated with these three IGT-specific metabolites by multiple interactions with four enzymes. The expression levels of these enzymes correlate with changes in the metabolite concentrations linked to diabetes. Our results may help developing novel strategies to prevent T2D.

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Three candidate metabolites for IGT associated with seven T2D-related genes. (A) Metabolites (white), enzymes (yellow), pathway-related proteins (gray) and T2D-related genes (blue) are represented with ellipses, rectangles, polygons and rounded rectangles, respectively. Arrows next to the ellipses and rectangles indicate altered metabolite concentrations in persons with IGT as compared with NGT, and enzyme activities in individuals with IGT. The 21 connections between metabolites, enzymes, pathway-related proteins and T2D-related genes were divided after visual inspections into four categories: physical interaction (purple solid line), transcription (blue dash line), signaling regulation (orange dash line) and same pathway (gray dot and dash line). The activation or inhibition is indicated. For further information, see Supplementary Table S12. (B) Log-transformed gene expression results of the probes of CAC, CrAT, ALAS-H and cPLA2 in 383 individuals with NGT, 104 with IGT and 26 patients with dT2D are shown from cross-sectional analysis of the KORA S4 survey. The P-values were adjusted for sex, age, BMI, physical activity, alcohol intake, smoking, systolic BP, HDL cholesterol, HbA1c and fasting glucose when IGT individuals were compared with NGT participants.
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f3: Three candidate metabolites for IGT associated with seven T2D-related genes. (A) Metabolites (white), enzymes (yellow), pathway-related proteins (gray) and T2D-related genes (blue) are represented with ellipses, rectangles, polygons and rounded rectangles, respectively. Arrows next to the ellipses and rectangles indicate altered metabolite concentrations in persons with IGT as compared with NGT, and enzyme activities in individuals with IGT. The 21 connections between metabolites, enzymes, pathway-related proteins and T2D-related genes were divided after visual inspections into four categories: physical interaction (purple solid line), transcription (blue dash line), signaling regulation (orange dash line) and same pathway (gray dot and dash line). The activation or inhibition is indicated. For further information, see Supplementary Table S12. (B) Log-transformed gene expression results of the probes of CAC, CrAT, ALAS-H and cPLA2 in 383 individuals with NGT, 104 with IGT and 26 patients with dT2D are shown from cross-sectional analysis of the KORA S4 survey. The P-values were adjusted for sex, age, BMI, physical activity, alcohol intake, smoking, systolic BP, HDL cholesterol, HbA1c and fasting glucose when IGT individuals were compared with NGT participants.

Mentions: To investigate the underlying molecular mechanism for the three identified IGT metabolites, we studied their associations with T2D-related genes by analyzing protein-metabolite interaction networks (Wishart et al, 2009; Szklarczyk et al, 2011). In all, 7 out of the 46 known T2D-related genes (PPARG, TCF7L2, HNF1A, GCK, IGF1, IRS1 and IDE) were linked to these metabolites through related enzymes or proteins (Figure 3A; the list of 46 genes is shown in Supplementary Table S13). To validate the networks, the links between metabolites, enzymes, pathway-related proteins and T2D-related genes were manually checked for biochemical relevance and classified into four groups: signaling regulation, transcription, physical interaction and the same pathway (Supplementary Table S14).


Novel biomarkers for pre-diabetes identified by metabolomics.

Wang-Sattler R, Yu Z, Herder C, Messias AC, Floegel A, He Y, Heim K, Campillos M, Holzapfel C, Thorand B, Grallert H, Xu T, Bader E, Huth C, Mittelstrass K, Döring A, Meisinger C, Gieger C, Prehn C, Roemisch-Margl W, Carstensen M, Xie L, Yamanaka-Okumura H, Xing G, Ceglarek U, Thiery J, Giani G, Lickert H, Lin X, Li Y, Boeing H, Joost HG, de Angelis MH, Rathmann W, Suhre K, Prokisch H, Peters A, Meitinger T, Roden M, Wichmann HE, Pischon T, Adamski J, Illig T - Mol. Syst. Biol. (2012)

Three candidate metabolites for IGT associated with seven T2D-related genes. (A) Metabolites (white), enzymes (yellow), pathway-related proteins (gray) and T2D-related genes (blue) are represented with ellipses, rectangles, polygons and rounded rectangles, respectively. Arrows next to the ellipses and rectangles indicate altered metabolite concentrations in persons with IGT as compared with NGT, and enzyme activities in individuals with IGT. The 21 connections between metabolites, enzymes, pathway-related proteins and T2D-related genes were divided after visual inspections into four categories: physical interaction (purple solid line), transcription (blue dash line), signaling regulation (orange dash line) and same pathway (gray dot and dash line). The activation or inhibition is indicated. For further information, see Supplementary Table S12. (B) Log-transformed gene expression results of the probes of CAC, CrAT, ALAS-H and cPLA2 in 383 individuals with NGT, 104 with IGT and 26 patients with dT2D are shown from cross-sectional analysis of the KORA S4 survey. The P-values were adjusted for sex, age, BMI, physical activity, alcohol intake, smoking, systolic BP, HDL cholesterol, HbA1c and fasting glucose when IGT individuals were compared with NGT participants.
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Related In: Results  -  Collection

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f3: Three candidate metabolites for IGT associated with seven T2D-related genes. (A) Metabolites (white), enzymes (yellow), pathway-related proteins (gray) and T2D-related genes (blue) are represented with ellipses, rectangles, polygons and rounded rectangles, respectively. Arrows next to the ellipses and rectangles indicate altered metabolite concentrations in persons with IGT as compared with NGT, and enzyme activities in individuals with IGT. The 21 connections between metabolites, enzymes, pathway-related proteins and T2D-related genes were divided after visual inspections into four categories: physical interaction (purple solid line), transcription (blue dash line), signaling regulation (orange dash line) and same pathway (gray dot and dash line). The activation or inhibition is indicated. For further information, see Supplementary Table S12. (B) Log-transformed gene expression results of the probes of CAC, CrAT, ALAS-H and cPLA2 in 383 individuals with NGT, 104 with IGT and 26 patients with dT2D are shown from cross-sectional analysis of the KORA S4 survey. The P-values were adjusted for sex, age, BMI, physical activity, alcohol intake, smoking, systolic BP, HDL cholesterol, HbA1c and fasting glucose when IGT individuals were compared with NGT participants.
Mentions: To investigate the underlying molecular mechanism for the three identified IGT metabolites, we studied their associations with T2D-related genes by analyzing protein-metabolite interaction networks (Wishart et al, 2009; Szklarczyk et al, 2011). In all, 7 out of the 46 known T2D-related genes (PPARG, TCF7L2, HNF1A, GCK, IGF1, IRS1 and IDE) were linked to these metabolites through related enzymes or proteins (Figure 3A; the list of 46 genes is shown in Supplementary Table S13). To validate the networks, the links between metabolites, enzymes, pathway-related proteins and T2D-related genes were manually checked for biochemical relevance and classified into four groups: signaling regulation, transcription, physical interaction and the same pathway (Supplementary Table S14).

Bottom Line: We identified three metabolites (glycine, lysophosphatidylcholine (LPC) (18:2) and acetylcarnitine) that had significantly altered levels in IGT individuals as compared to those with normal glucose tolerance, with P-values ranging from 2.4×10(-4) to 2.1×10(-13).Lower levels of glycine and LPC were found to be predictors not only for IGT but also for T2D, and were independently confirmed in the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam cohort.Our results may help developing novel strategies to prevent T2D.

View Article: PubMed Central - PubMed

Affiliation: Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany. rui.wang-sattler@helmholtz-muenchen.de

ABSTRACT
Type 2 diabetes (T2D) can be prevented in pre-diabetic individuals with impaired glucose tolerance (IGT). Here, we have used a metabolomics approach to identify candidate biomarkers of pre-diabetes. We quantified 140 metabolites for 4297 fasting serum samples in the population-based Cooperative Health Research in the Region of Augsburg (KORA) cohort. Our study revealed significant metabolic variation in pre-diabetic individuals that are distinct from known diabetes risk indicators, such as glycosylated hemoglobin levels, fasting glucose and insulin. We identified three metabolites (glycine, lysophosphatidylcholine (LPC) (18:2) and acetylcarnitine) that had significantly altered levels in IGT individuals as compared to those with normal glucose tolerance, with P-values ranging from 2.4×10(-4) to 2.1×10(-13). Lower levels of glycine and LPC were found to be predictors not only for IGT but also for T2D, and were independently confirmed in the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam cohort. Using metabolite-protein network analysis, we identified seven T2D-related genes that are associated with these three IGT-specific metabolites by multiple interactions with four enzymes. The expression levels of these enzymes correlate with changes in the metabolite concentrations linked to diabetes. Our results may help developing novel strategies to prevent T2D.

Show MeSH
Related in: MedlinePlus