Metabolite ratios as potential biomarkers for type 2 diabetes: a DIRECT study

Sophie Molnos, Simone Wahl, Mark Haid, E. Marelise W. Eekhoff, René Pool, Anna Floegel, Joris Deelen, Daniela Much, Cornelia Prehn, Michaela Breier, Harmen H. Draisma, Nienke van Leeuwen, Annemarie M.C. Simonis-Bik, Anna Elisabet Jonsson, Gonneke Willemsen, Wolfgang Bernigau, Rui Wang-Sattler, Karsten Suhre, Annette Peters, Barbara ThorandChristian Herder, Wolfgang Rathmann, Michael Roden, Christian Gieger, Mark H.H. Kramer, Diana van Heemst, Helle Krogh Pedersen, Valborg Gudmundsdottir, Matthias B. Schulze, Tobias Pischon, Eco J.C. de Geus, Heiner Boeing, Dorret I. Boomsma, Anette G. Ziegler, P. Eline Slagboom, Sandra Hummel, Marian Beekman, Harald Grallert, Søren Brunak, Mark I. McCarthy, Ramneek Gupta, Ewan R. Pearson, Jerzy Adamski, Leen M. 'T Hart*

*Corresponding author for this work

    Research output: Contribution to journalJournal articleResearchpeer-review

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    Abstract

    Aims/hypothesis: Circulating metabolites have been shown to reflect metabolic changes during the development of type 2 diabetes. In this study we examined the association of metabolite levels and pairwise metabolite ratios with insulin responses after glucose, glucagon-like peptide-1 (GLP-1) and arginine stimulation. We then investigated if the identified metabolite ratios were associated with measures of OGTT-derived beta cell function and with prevalent and incident type 2 diabetes. Methods: We measured the levels of 188 metabolites in plasma samples from 130 healthy members of twin families (from the Netherlands Twin Register) at five time points during a modified 3 h hyperglycaemic clamp with glucose, GLP-1 and arginine stimulation. We validated our results in cohorts with OGTT data (n = 340) and epidemiological case–control studies of prevalent (n = 4925) and incident (n = 4277) diabetes. The data were analysed using regression models with adjustment for potential confounders. Results: There were dynamic changes in metabolite levels in response to the different secretagogues. Furthermore, several fasting pairwise metabolite ratios were associated with one or multiple clamp-derived measures of insulin secretion (all p <9.2 × 10−7). These associations were significantly stronger compared with the individual metabolite components. One of the ratios, valine to phosphatidylcholine acyl-alkyl C32:2 (PC ae C32:2), in addition showed a directionally consistent positive association with OGTT-derived measures of insulin secretion and resistance (p ≤ 5.4 × 10−3) and prevalent type 2 diabetes (ORVal_PC ae C32:2 2.64 [β 0.97 ± 0.09], p = 1.0 × 10−27). Furthermore, Val_PC ae C32:2 predicted incident diabetes independent of established risk factors in two epidemiological cohort studies (HRVal_PC ae C32:2 1.57 [β 0.45 ± 0.06]; p = 1.3 × 10−15), leading to modest improvements in the receiver operating characteristics when added to a model containing a set of established risk factors in both cohorts (increases from 0.780 to 0.801 and from 0.862 to 0.865 respectively, when added to the model containing traditional risk factors + glucose). Conclusions/interpretation: In this study we have shown that the Val_PC ae C32:2 metabolite ratio is associated with an increased risk of type 2 diabetes and measures of insulin secretion and resistance. The observed effects were stronger than that of the individual metabolites and independent of known risk factors.
    Original languageEnglish
    JournalDiabetologia
    Volume61
    Pages (from-to)117-129
    ISSN0012-186X
    DOIs
    Publication statusPublished - 2018

    Keywords

    • Epidemiology
    • Insulin secretion
    • Metabolomics
    • Prediction of diabetes
    • Type 2 diabetes

    Cite this

    Molnos, S., Wahl, S., Haid, M., Eekhoff, E. M. W., Pool, R., Floegel, A., ... 'T Hart, L. M. (2018). Metabolite ratios as potential biomarkers for type 2 diabetes: a DIRECT study. Diabetologia, 61, 117-129. https://doi.org/10.1007/s00125-017-4436-7
    Molnos, Sophie ; Wahl, Simone ; Haid, Mark ; Eekhoff, E. Marelise W. ; Pool, René ; Floegel, Anna ; Deelen, Joris ; Much, Daniela ; Prehn, Cornelia ; Breier, Michaela ; Draisma, Harmen H. ; van Leeuwen, Nienke ; Simonis-Bik, Annemarie M.C. ; Jonsson, Anna Elisabet ; Willemsen, Gonneke ; Bernigau, Wolfgang ; Wang-Sattler, Rui ; Suhre, Karsten ; Peters, Annette ; Thorand, Barbara ; Herder, Christian ; Rathmann, Wolfgang ; Roden, Michael ; Gieger, Christian ; Kramer, Mark H.H. ; van Heemst, Diana ; Pedersen, Helle Krogh ; Gudmundsdottir, Valborg ; Schulze, Matthias B. ; Pischon, Tobias ; de Geus, Eco J.C. ; Boeing, Heiner ; Boomsma, Dorret I. ; Ziegler, Anette G. ; Slagboom, P. Eline ; Hummel, Sandra ; Beekman, Marian ; Grallert, Harald ; Brunak, Søren ; McCarthy, Mark I. ; Gupta, Ramneek ; Pearson, Ewan R. ; Adamski, Jerzy ; 'T Hart, Leen M. / Metabolite ratios as potential biomarkers for type 2 diabetes: a DIRECT study. In: Diabetologia. 2018 ; Vol. 61. pp. 117-129.
    @article{f5ff367d1c6149d7aa9152f502969e54,
    title = "Metabolite ratios as potential biomarkers for type 2 diabetes: a DIRECT study",
    abstract = "Aims/hypothesis: Circulating metabolites have been shown to reflect metabolic changes during the development of type 2 diabetes. In this study we examined the association of metabolite levels and pairwise metabolite ratios with insulin responses after glucose, glucagon-like peptide-1 (GLP-1) and arginine stimulation. We then investigated if the identified metabolite ratios were associated with measures of OGTT-derived beta cell function and with prevalent and incident type 2 diabetes. Methods: We measured the levels of 188 metabolites in plasma samples from 130 healthy members of twin families (from the Netherlands Twin Register) at five time points during a modified 3 h hyperglycaemic clamp with glucose, GLP-1 and arginine stimulation. We validated our results in cohorts with OGTT data (n = 340) and epidemiological case{\^a}€“control studies of prevalent (n = 4925) and incident (n = 4277) diabetes. The data were analysed using regression models with adjustment for potential confounders. Results: There were dynamic changes in metabolite levels in response to the different secretagogues. Furthermore, several fasting pairwise metabolite ratios were associated with one or multiple clamp-derived measures of insulin secretion (all p <9.2 {\~A}— 10{\^a}ˆ’7). These associations were significantly stronger compared with the individual metabolite components. One of the ratios, valine to phosphatidylcholine acyl-alkyl C32:2 (PC ae C32:2), in addition showed a directionally consistent positive association with OGTT-derived measures of insulin secretion and resistance (p {\^a}‰¤ 5.4 {\~A}— 10{\^a}ˆ’3) and prevalent type 2 diabetes (ORVal_PC ae C32:2 2.64 [{\^I}² 0.97 {\^A}± 0.09], p = 1.0 {\~A}— 10{\^a}ˆ’27). Furthermore, Val_PC ae C32:2 predicted incident diabetes independent of established risk factors in two epidemiological cohort studies (HRVal_PC ae C32:2 1.57 [{\^I}² 0.45 {\^A}± 0.06]; p = 1.3 {\~A}— 10{\^a}ˆ’15), leading to modest improvements in the receiver operating characteristics when added to a model containing a set of established risk factors in both cohorts (increases from 0.780 to 0.801 and from 0.862 to 0.865 respectively, when added to the model containing traditional risk factors + glucose). Conclusions/interpretation: In this study we have shown that the Val_PC ae C32:2 metabolite ratio is associated with an increased risk of type 2 diabetes and measures of insulin secretion and resistance. The observed effects were stronger than that of the individual metabolites and independent of known risk factors.",
    keywords = "Epidemiology, Insulin secretion, Metabolomics, Prediction of diabetes, Type 2 diabetes",
    author = "Sophie Molnos and Simone Wahl and Mark Haid and Eekhoff, {E. Marelise W.} and Ren{\'e} Pool and Anna Floegel and Joris Deelen and Daniela Much and Cornelia Prehn and Michaela Breier and Draisma, {Harmen H.} and {van Leeuwen}, Nienke and Simonis-Bik, {Annemarie M.C.} and Jonsson, {Anna Elisabet} and Gonneke Willemsen and Wolfgang Bernigau and Rui Wang-Sattler and Karsten Suhre and Annette Peters and Barbara Thorand and Christian Herder and Wolfgang Rathmann and Michael Roden and Christian Gieger and Kramer, {Mark H.H.} and {van Heemst}, Diana and Pedersen, {Helle Krogh} and Valborg Gudmundsdottir and Schulze, {Matthias B.} and Tobias Pischon and {de Geus}, {Eco J.C.} and Heiner Boeing and Boomsma, {Dorret I.} and Ziegler, {Anette G.} and Slagboom, {P. Eline} and Sandra Hummel and Marian Beekman and Harald Grallert and S{\o}ren Brunak and McCarthy, {Mark I.} and Ramneek Gupta and Pearson, {Ewan R.} and Jerzy Adamski and {'T Hart}, {Leen M.}",
    year = "2018",
    doi = "10.1007/s00125-017-4436-7",
    language = "English",
    volume = "61",
    pages = "117--129",
    journal = "Diabetologia",
    issn = "0012-186X",
    publisher = "Springer",

    }

    Molnos, S, Wahl, S, Haid, M, Eekhoff, EMW, Pool, R, Floegel, A, Deelen, J, Much, D, Prehn, C, Breier, M, Draisma, HH, van Leeuwen, N, Simonis-Bik, AMC, Jonsson, AE, Willemsen, G, Bernigau, W, Wang-Sattler, R, Suhre, K, Peters, A, Thorand, B, Herder, C, Rathmann, W, Roden, M, Gieger, C, Kramer, MHH, van Heemst, D, Pedersen, HK, Gudmundsdottir, V, Schulze, MB, Pischon, T, de Geus, EJC, Boeing, H, Boomsma, DI, Ziegler, AG, Slagboom, PE, Hummel, S, Beekman, M, Grallert, H, Brunak, S, McCarthy, MI, Gupta, R, Pearson, ER, Adamski, J & 'T Hart, LM 2018, 'Metabolite ratios as potential biomarkers for type 2 diabetes: a DIRECT study', Diabetologia, vol. 61, pp. 117-129. https://doi.org/10.1007/s00125-017-4436-7

    Metabolite ratios as potential biomarkers for type 2 diabetes: a DIRECT study. / Molnos, Sophie; Wahl, Simone; Haid, Mark; Eekhoff, E. Marelise W.; Pool, René; Floegel, Anna; Deelen, Joris; Much, Daniela; Prehn, Cornelia; Breier, Michaela; Draisma, Harmen H.; van Leeuwen, Nienke; Simonis-Bik, Annemarie M.C.; Jonsson, Anna Elisabet; Willemsen, Gonneke; Bernigau, Wolfgang; Wang-Sattler, Rui; Suhre, Karsten; Peters, Annette; Thorand, Barbara; Herder, Christian; Rathmann, Wolfgang; Roden, Michael; Gieger, Christian; Kramer, Mark H.H.; van Heemst, Diana; Pedersen, Helle Krogh; Gudmundsdottir, Valborg; Schulze, Matthias B.; Pischon, Tobias; de Geus, Eco J.C.; Boeing, Heiner; Boomsma, Dorret I.; Ziegler, Anette G.; Slagboom, P. Eline; Hummel, Sandra; Beekman, Marian; Grallert, Harald; Brunak, Søren; McCarthy, Mark I.; Gupta, Ramneek; Pearson, Ewan R.; Adamski, Jerzy; 'T Hart, Leen M.

    In: Diabetologia, Vol. 61, 2018, p. 117-129.

    Research output: Contribution to journalJournal articleResearchpeer-review

    TY - JOUR

    T1 - Metabolite ratios as potential biomarkers for type 2 diabetes: a DIRECT study

    AU - Molnos, Sophie

    AU - Wahl, Simone

    AU - Haid, Mark

    AU - Eekhoff, E. Marelise W.

    AU - Pool, René

    AU - Floegel, Anna

    AU - Deelen, Joris

    AU - Much, Daniela

    AU - Prehn, Cornelia

    AU - Breier, Michaela

    AU - Draisma, Harmen H.

    AU - van Leeuwen, Nienke

    AU - Simonis-Bik, Annemarie M.C.

    AU - Jonsson, Anna Elisabet

    AU - Willemsen, Gonneke

    AU - Bernigau, Wolfgang

    AU - Wang-Sattler, Rui

    AU - Suhre, Karsten

    AU - Peters, Annette

    AU - Thorand, Barbara

    AU - Herder, Christian

    AU - Rathmann, Wolfgang

    AU - Roden, Michael

    AU - Gieger, Christian

    AU - Kramer, Mark H.H.

    AU - van Heemst, Diana

    AU - Pedersen, Helle Krogh

    AU - Gudmundsdottir, Valborg

    AU - Schulze, Matthias B.

    AU - Pischon, Tobias

    AU - de Geus, Eco J.C.

    AU - Boeing, Heiner

    AU - Boomsma, Dorret I.

    AU - Ziegler, Anette G.

    AU - Slagboom, P. Eline

    AU - Hummel, Sandra

    AU - Beekman, Marian

    AU - Grallert, Harald

    AU - Brunak, Søren

    AU - McCarthy, Mark I.

    AU - Gupta, Ramneek

    AU - Pearson, Ewan R.

    AU - Adamski, Jerzy

    AU - 'T Hart, Leen M.

    PY - 2018

    Y1 - 2018

    N2 - Aims/hypothesis: Circulating metabolites have been shown to reflect metabolic changes during the development of type 2 diabetes. In this study we examined the association of metabolite levels and pairwise metabolite ratios with insulin responses after glucose, glucagon-like peptide-1 (GLP-1) and arginine stimulation. We then investigated if the identified metabolite ratios were associated with measures of OGTT-derived beta cell function and with prevalent and incident type 2 diabetes. Methods: We measured the levels of 188 metabolites in plasma samples from 130 healthy members of twin families (from the Netherlands Twin Register) at five time points during a modified 3 h hyperglycaemic clamp with glucose, GLP-1 and arginine stimulation. We validated our results in cohorts with OGTT data (n = 340) and epidemiological case–control studies of prevalent (n = 4925) and incident (n = 4277) diabetes. The data were analysed using regression models with adjustment for potential confounders. Results: There were dynamic changes in metabolite levels in response to the different secretagogues. Furthermore, several fasting pairwise metabolite ratios were associated with one or multiple clamp-derived measures of insulin secretion (all p <9.2 × 10−7). These associations were significantly stronger compared with the individual metabolite components. One of the ratios, valine to phosphatidylcholine acyl-alkyl C32:2 (PC ae C32:2), in addition showed a directionally consistent positive association with OGTT-derived measures of insulin secretion and resistance (p ≤ 5.4 × 10−3) and prevalent type 2 diabetes (ORVal_PC ae C32:2 2.64 [β 0.97 ± 0.09], p = 1.0 × 10−27). Furthermore, Val_PC ae C32:2 predicted incident diabetes independent of established risk factors in two epidemiological cohort studies (HRVal_PC ae C32:2 1.57 [β 0.45 ± 0.06]; p = 1.3 × 10−15), leading to modest improvements in the receiver operating characteristics when added to a model containing a set of established risk factors in both cohorts (increases from 0.780 to 0.801 and from 0.862 to 0.865 respectively, when added to the model containing traditional risk factors + glucose). Conclusions/interpretation: In this study we have shown that the Val_PC ae C32:2 metabolite ratio is associated with an increased risk of type 2 diabetes and measures of insulin secretion and resistance. The observed effects were stronger than that of the individual metabolites and independent of known risk factors.

    AB - Aims/hypothesis: Circulating metabolites have been shown to reflect metabolic changes during the development of type 2 diabetes. In this study we examined the association of metabolite levels and pairwise metabolite ratios with insulin responses after glucose, glucagon-like peptide-1 (GLP-1) and arginine stimulation. We then investigated if the identified metabolite ratios were associated with measures of OGTT-derived beta cell function and with prevalent and incident type 2 diabetes. Methods: We measured the levels of 188 metabolites in plasma samples from 130 healthy members of twin families (from the Netherlands Twin Register) at five time points during a modified 3 h hyperglycaemic clamp with glucose, GLP-1 and arginine stimulation. We validated our results in cohorts with OGTT data (n = 340) and epidemiological case–control studies of prevalent (n = 4925) and incident (n = 4277) diabetes. The data were analysed using regression models with adjustment for potential confounders. Results: There were dynamic changes in metabolite levels in response to the different secretagogues. Furthermore, several fasting pairwise metabolite ratios were associated with one or multiple clamp-derived measures of insulin secretion (all p <9.2 × 10−7). These associations were significantly stronger compared with the individual metabolite components. One of the ratios, valine to phosphatidylcholine acyl-alkyl C32:2 (PC ae C32:2), in addition showed a directionally consistent positive association with OGTT-derived measures of insulin secretion and resistance (p ≤ 5.4 × 10−3) and prevalent type 2 diabetes (ORVal_PC ae C32:2 2.64 [β 0.97 ± 0.09], p = 1.0 × 10−27). Furthermore, Val_PC ae C32:2 predicted incident diabetes independent of established risk factors in two epidemiological cohort studies (HRVal_PC ae C32:2 1.57 [β 0.45 ± 0.06]; p = 1.3 × 10−15), leading to modest improvements in the receiver operating characteristics when added to a model containing a set of established risk factors in both cohorts (increases from 0.780 to 0.801 and from 0.862 to 0.865 respectively, when added to the model containing traditional risk factors + glucose). Conclusions/interpretation: In this study we have shown that the Val_PC ae C32:2 metabolite ratio is associated with an increased risk of type 2 diabetes and measures of insulin secretion and resistance. The observed effects were stronger than that of the individual metabolites and independent of known risk factors.

    KW - Epidemiology

    KW - Insulin secretion

    KW - Metabolomics

    KW - Prediction of diabetes

    KW - Type 2 diabetes

    U2 - 10.1007/s00125-017-4436-7

    DO - 10.1007/s00125-017-4436-7

    M3 - Journal article

    C2 - 28936587

    VL - 61

    SP - 117

    EP - 129

    JO - Diabetologia

    JF - Diabetologia

    SN - 0012-186X

    ER -