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The use of metabolic profiling to identify insulin resistance in veal calves

Heavy veal calves (4–6 months old) are at risk of developing insulin resistance and disturbed glucose homeostasis. Prolonged insulin resistance could lead to metabolic disorders and impaired growth performance. Recently, we discovered that heavy Holstein-Friesian calves raised on a high-lactose or h...

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Autores principales: Pantophlet, Andre J., Roelofsen, Han, de Vries, Marcel P., Gerrits, Walter J. J., van den Borne, Joost J. G. C., Vonk, Roel J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5472311/
https://www.ncbi.nlm.nih.gov/pubmed/28617863
http://dx.doi.org/10.1371/journal.pone.0179612
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author Pantophlet, Andre J.
Roelofsen, Han
de Vries, Marcel P.
Gerrits, Walter J. J.
van den Borne, Joost J. G. C.
Vonk, Roel J.
author_facet Pantophlet, Andre J.
Roelofsen, Han
de Vries, Marcel P.
Gerrits, Walter J. J.
van den Borne, Joost J. G. C.
Vonk, Roel J.
author_sort Pantophlet, Andre J.
collection PubMed
description Heavy veal calves (4–6 months old) are at risk of developing insulin resistance and disturbed glucose homeostasis. Prolonged insulin resistance could lead to metabolic disorders and impaired growth performance. Recently, we discovered that heavy Holstein-Friesian calves raised on a high-lactose or high-fat diet did not differ in insulin sensitivity, that insulin sensitivity was low and 50% of the calves could be considered insulin resistant. Understanding the patho-physiological mechanisms underlying insulin resistance and discovering biomarkers for early diagnosis would be useful for developing prevention strategies. Therefore, we explored plasma metabolic profiling techniques to build models and discover potential biomarkers and pathways that can distinguish between insulin resistant and moderately insulin sensitive veal calves. The calves (n = 14) were classified as insulin resistant (IR) or moderately insulin sensitive (MIS) based on results from a euglycemic-hyperinsulinemic clamp, using a cut-off value (M/I-value <4.4) to identify insulin resistance. Metabolic profiles of fasting plasma samples were analyzed using reversed phase (RP) and hydrophilic interaction (HILIC) liquid chromatography–mass spectrometry (LC-MS). Orthogonal partial least square discriminant analysis was performed to compare metabolic profiles. Insulin sensitivity was on average 2.3x higher (P <0.001) in MIS than IR group. For both RP-LC-MS and HILIC-LC-MS satisfactory models were build (R(2)Y >90% and Q(2)Y >66%), which allowed discrimination between MIS and IR calves. A total of 7 and 20 metabolic features (for RP-LC-MS and HILIC-LC-MS respectively) were most responsible for group separation. Of these, 7 metabolites could putatively be identified that differed (P <0.05) between groups (potential biomarkers). Pathway analysis indicated disturbances in glycerophospholipid and sphingolipid metabolism, the glycine, serine and threonine metabolism, and primary bile acid biosynthesis. These results demonstrate that plasma metabolic profiling can be used to identify insulin resistance in veal calves and can lead to underlying mechanisms.
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spelling pubmed-54723112017-07-03 The use of metabolic profiling to identify insulin resistance in veal calves Pantophlet, Andre J. Roelofsen, Han de Vries, Marcel P. Gerrits, Walter J. J. van den Borne, Joost J. G. C. Vonk, Roel J. PLoS One Research Article Heavy veal calves (4–6 months old) are at risk of developing insulin resistance and disturbed glucose homeostasis. Prolonged insulin resistance could lead to metabolic disorders and impaired growth performance. Recently, we discovered that heavy Holstein-Friesian calves raised on a high-lactose or high-fat diet did not differ in insulin sensitivity, that insulin sensitivity was low and 50% of the calves could be considered insulin resistant. Understanding the patho-physiological mechanisms underlying insulin resistance and discovering biomarkers for early diagnosis would be useful for developing prevention strategies. Therefore, we explored plasma metabolic profiling techniques to build models and discover potential biomarkers and pathways that can distinguish between insulin resistant and moderately insulin sensitive veal calves. The calves (n = 14) were classified as insulin resistant (IR) or moderately insulin sensitive (MIS) based on results from a euglycemic-hyperinsulinemic clamp, using a cut-off value (M/I-value <4.4) to identify insulin resistance. Metabolic profiles of fasting plasma samples were analyzed using reversed phase (RP) and hydrophilic interaction (HILIC) liquid chromatography–mass spectrometry (LC-MS). Orthogonal partial least square discriminant analysis was performed to compare metabolic profiles. Insulin sensitivity was on average 2.3x higher (P <0.001) in MIS than IR group. For both RP-LC-MS and HILIC-LC-MS satisfactory models were build (R(2)Y >90% and Q(2)Y >66%), which allowed discrimination between MIS and IR calves. A total of 7 and 20 metabolic features (for RP-LC-MS and HILIC-LC-MS respectively) were most responsible for group separation. Of these, 7 metabolites could putatively be identified that differed (P <0.05) between groups (potential biomarkers). Pathway analysis indicated disturbances in glycerophospholipid and sphingolipid metabolism, the glycine, serine and threonine metabolism, and primary bile acid biosynthesis. These results demonstrate that plasma metabolic profiling can be used to identify insulin resistance in veal calves and can lead to underlying mechanisms. Public Library of Science 2017-06-15 /pmc/articles/PMC5472311/ /pubmed/28617863 http://dx.doi.org/10.1371/journal.pone.0179612 Text en © 2017 Pantophlet et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Pantophlet, Andre J.
Roelofsen, Han
de Vries, Marcel P.
Gerrits, Walter J. J.
van den Borne, Joost J. G. C.
Vonk, Roel J.
The use of metabolic profiling to identify insulin resistance in veal calves
title The use of metabolic profiling to identify insulin resistance in veal calves
title_full The use of metabolic profiling to identify insulin resistance in veal calves
title_fullStr The use of metabolic profiling to identify insulin resistance in veal calves
title_full_unstemmed The use of metabolic profiling to identify insulin resistance in veal calves
title_short The use of metabolic profiling to identify insulin resistance in veal calves
title_sort use of metabolic profiling to identify insulin resistance in veal calves
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5472311/
https://www.ncbi.nlm.nih.gov/pubmed/28617863
http://dx.doi.org/10.1371/journal.pone.0179612
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