InsuTAG: a novel physiologically relevant predictor for insulin resistance and metabolic syndrome

Rohith N. Thota; Kylie A. Abbott; Jessica J. A. Ferguson; Martin Veysey; Mark Lucock; Suzanne Niblett; Katrina King; Manohar L. Garg

doi:10.1038/s41598-017-15460-z

InsuTAG: a novel physiologically relevant predictor for insulin resistance and metabolic syndrome

Rohith N. Thota, Kylie A. Abbott, Jessica J. A. Ferguson, Martin Veysey, Mark Lucock, Suzanne Niblett, Katrina King, Manohar L. Garg

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Abstract

The aim of this study was to investigate whether a novel physiologically relevant marker, InsuTAG (fasting insulin × fasting triglycerides) can predict insulin resistance (IR) and metabolic syndrome (MetS). Data of 618 participants from the Retirement Health and Lifestyle Study (RHLS) were evaluated for the current study. IR was defined by homeostatic model assessment (HOMA-IR) scores. Pearson correlations were used to examine the associations of InsuTAG with HOMA-IR and other markers. Predictions of IR from InsuTAG were evaluated using multiple regression models. Receiver operating characteristic curves (ROC) were constructed to measure the sensitivity and specificity of InsuTAG values and to determine the optimum cut-off point for prediction of IR. InsuTAG was positively correlated with HOMA-IR (r = 0.86; p < 0.0001). InsuTAG is a strong predictor of IR accounting for 65.0% of the variation in HOMA-IR values after adjusting for potential confounders. Areas under the ROC curve showed that InsuTAG (0.93) has higher value than other known lipid markers for predicting IR, with a sensitivity and specificity of 84.15% and 86.88%. Prevalence of MetS was significantly (p < 0.0001) higher in subjects with InsuTAG values greater than optimal cut-off value of 11.2. Thus, InsuTAG appears to be a potential feasible marker of IR and metabolic syndrome.

Original language	English
Article number	15204
Pages (from-to)	1-10
Number of pages	10
Journal	Scientific Reports
Volume	7
DOIs	https://doi.org/10.1038/s41598-017-15460-z
Publication status	Published - Dec 2017
Externally published	Yes

Bibliographical note

Copyright the Author(s) 2017. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.

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Publisher version (open access)Final published version, 1.3 MBLicence: CC BY

Cite this

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title = "InsuTAG: a novel physiologically relevant predictor for insulin resistance and metabolic syndrome",

abstract = "The aim of this study was to investigate whether a novel physiologically relevant marker, InsuTAG (fasting insulin × fasting triglycerides) can predict insulin resistance (IR) and metabolic syndrome (MetS). Data of 618 participants from the Retirement Health and Lifestyle Study (RHLS) were evaluated for the current study. IR was defined by homeostatic model assessment (HOMA-IR) scores. Pearson correlations were used to examine the associations of InsuTAG with HOMA-IR and other markers. Predictions of IR from InsuTAG were evaluated using multiple regression models. Receiver operating characteristic curves (ROC) were constructed to measure the sensitivity and specificity of InsuTAG values and to determine the optimum cut-off point for prediction of IR. InsuTAG was positively correlated with HOMA-IR (r = 0.86; p < 0.0001). InsuTAG is a strong predictor of IR accounting for 65.0% of the variation in HOMA-IR values after adjusting for potential confounders. Areas under the ROC curve showed that InsuTAG (0.93) has higher value than other known lipid markers for predicting IR, with a sensitivity and specificity of 84.15% and 86.88%. Prevalence of MetS was significantly (p < 0.0001) higher in subjects with InsuTAG values greater than optimal cut-off value of 11.2. Thus, InsuTAG appears to be a potential feasible marker of IR and metabolic syndrome.",

author = "Thota, {Rohith N.} and Abbott, {Kylie A.} and Ferguson, {Jessica J. A.} and Martin Veysey and Mark Lucock and Suzanne Niblett and Katrina King and Garg, {Manohar L.}",

note = "Copyright the Author(s) 2017. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.",

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month = dec,

doi = "10.1038/s41598-017-15460-z",

language = "English",

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T2 - a novel physiologically relevant predictor for insulin resistance and metabolic syndrome

AU - Thota, Rohith N.

AU - Abbott, Kylie A.

AU - Ferguson, Jessica J. A.

AU - Veysey, Martin

AU - Lucock, Mark

AU - Niblett, Suzanne

AU - King, Katrina

AU - Garg, Manohar L.

N1 - Copyright the Author(s) 2017. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.

PY - 2017/12

Y1 - 2017/12

N2 - The aim of this study was to investigate whether a novel physiologically relevant marker, InsuTAG (fasting insulin × fasting triglycerides) can predict insulin resistance (IR) and metabolic syndrome (MetS). Data of 618 participants from the Retirement Health and Lifestyle Study (RHLS) were evaluated for the current study. IR was defined by homeostatic model assessment (HOMA-IR) scores. Pearson correlations were used to examine the associations of InsuTAG with HOMA-IR and other markers. Predictions of IR from InsuTAG were evaluated using multiple regression models. Receiver operating characteristic curves (ROC) were constructed to measure the sensitivity and specificity of InsuTAG values and to determine the optimum cut-off point for prediction of IR. InsuTAG was positively correlated with HOMA-IR (r = 0.86; p < 0.0001). InsuTAG is a strong predictor of IR accounting for 65.0% of the variation in HOMA-IR values after adjusting for potential confounders. Areas under the ROC curve showed that InsuTAG (0.93) has higher value than other known lipid markers for predicting IR, with a sensitivity and specificity of 84.15% and 86.88%. Prevalence of MetS was significantly (p < 0.0001) higher in subjects with InsuTAG values greater than optimal cut-off value of 11.2. Thus, InsuTAG appears to be a potential feasible marker of IR and metabolic syndrome.

AB - The aim of this study was to investigate whether a novel physiologically relevant marker, InsuTAG (fasting insulin × fasting triglycerides) can predict insulin resistance (IR) and metabolic syndrome (MetS). Data of 618 participants from the Retirement Health and Lifestyle Study (RHLS) were evaluated for the current study. IR was defined by homeostatic model assessment (HOMA-IR) scores. Pearson correlations were used to examine the associations of InsuTAG with HOMA-IR and other markers. Predictions of IR from InsuTAG were evaluated using multiple regression models. Receiver operating characteristic curves (ROC) were constructed to measure the sensitivity and specificity of InsuTAG values and to determine the optimum cut-off point for prediction of IR. InsuTAG was positively correlated with HOMA-IR (r = 0.86; p < 0.0001). InsuTAG is a strong predictor of IR accounting for 65.0% of the variation in HOMA-IR values after adjusting for potential confounders. Areas under the ROC curve showed that InsuTAG (0.93) has higher value than other known lipid markers for predicting IR, with a sensitivity and specificity of 84.15% and 86.88%. Prevalence of MetS was significantly (p < 0.0001) higher in subjects with InsuTAG values greater than optimal cut-off value of 11.2. Thus, InsuTAG appears to be a potential feasible marker of IR and metabolic syndrome.

U2 - 10.1038/s41598-017-15460-z

DO - 10.1038/s41598-017-15460-z

M3 - Article

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SN - 2045-2322

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SP - 1

EP - 10

JO - Scientific Reports

JF - Scientific Reports

M1 - 15204

ER -

InsuTAG: a novel physiologically relevant predictor for insulin resistance and metabolic syndrome

Abstract

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