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 Jonsson, Gonneke Willemsen, Wolfgang Bernigau, Rui Wang-Sattler, Karsten Suhre, Annette Peters, Barbara Thorand & 24 others Christian Herder, Wolfgang Rathmann, Michael Roden, Christian Gieger, Mark H.H. Kramer, Diana van Heemst, Helle K. 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

Research output: Contribution to journalArticleAcademicpeer-review

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
Pages (from-to)117-129
Number of pages13
JournalDiabetologia
Volume61
Issue number1
DOIs
Publication statusPublished - Jan 2018

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(1), 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 ; 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 K. ; 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, No. 1. pp. 117-129.
@article{79f9d53d2fdc454dbfcc283b2750a0b7,
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–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.",
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 Anna Jonsson 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 K.} 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",
month = "1",
doi = "10.1007/s00125-017-4436-7",
language = "English",
volume = "61",
pages = "117--129",
journal = "Diabetologia",
issn = "0012-186X",
publisher = "Springer Verlag",
number = "1",

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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, A, 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, no. 1, 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; 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 K.; 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, No. 1, 01.2018, p. 117-129.

Research output: Contribution to journalArticleAcademicpeer-review

TY - JOUR

T1 - Metabolite ratios as potential biomarkers for type 2 diabetes

T2 - 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

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 K.

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 - 2018/1

Y1 - 2018/1

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

UR - http://www.scopus.com/inward/record.url?scp=85029711516&partnerID=8YFLogxK

U2 - 10.1007/s00125-017-4436-7

DO - 10.1007/s00125-017-4436-7

M3 - Article

VL - 61

SP - 117

EP - 129

JO - Diabetologia

JF - Diabetologia

SN - 0012-186X

IS - 1

ER -