α-Hydroxybutyrate Is an Early Biomarker of Insulin Resistance and Glucose Intolerance in a Nondiabetic Population

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Abstract

Background

Insulin resistance is a risk factor for type 2 diabetes and cardiovascular disease progression. Current diagnostic tests, such as glycemic indicators, have limitations in the early detection of insulin resistant individuals. We searched for novel biomarkers identifying these at-risk subjects.

Methods

Using mass spectrometry, non-targeted biochemical profiling was conducted in a cohort of 399 nondiabetic subjects representing a broad spectrum of insulin sensitivity and glucose tolerance (based on the hyperinsulinemic euglycemic clamp and oral glucose tolerance testing, respectively).

Results

Random forest statistical analysis selected α-hydroxybutyrate (α–HB) as the top-ranked biochemical for separating insulin resistant (lower third of the clamp-derived M _FFM = 33 [12] µmol·min ⁻¹·kg _FFM ⁻¹, median [interquartile range], n = 140) from insulin sensitive subjects (M _FFM = 66 [23] µmol·min ⁻¹·kg _FFM ⁻¹) with a 76% accuracy. By targeted isotope dilution assay, plasma α–HB concentrations were reciprocally related to M _FFM; and by partition analysis, an α–HB value of 5 µg/ml was found to best separate insulin resistant from insulin sensitive subjects. α–HB also separated subjects with normal glucose tolerance from those with impaired fasting glycemia or impaired glucose tolerance independently of, and in an additive fashion to, insulin resistance. These associations were also independent of sex, age and BMI. Other metabolites from this global analysis that significantly correlated to insulin sensitivity included certain organic acid, amino acid, lysophospholipid, acylcarnitine and fatty acid species. Several metabolites are intermediates related to α-HB metabolism and biosynthesis.

Conclusions

α–hydroxybutyrate is an early marker for both insulin resistance and impaired glucose regulation. The underlying biochemical mechanisms may involve increased lipid oxidation and oxidative stress.

Related collections

Most cited references 34

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Metabolomic profiles delineate potential role for sarcosine in prostate cancer progression.

Arun Sreekumar, Laila Poisson, Thekkelnaycke M Rajendiran … (2009)

Multiple, complex molecular events characterize cancer development and progression. Deciphering the molecular networks that distinguish organ-confined disease from metastatic disease may lead to the identification of critical biomarkers for cancer invasion and disease aggressiveness. Although gene and protein expression have been extensively profiled in human tumours, little is known about the global metabolomic alterations that characterize neoplastic progression. Using a combination of high-throughput liquid-and-gas-chromatography-based mass spectrometry, we profiled more than 1,126 metabolites across 262 clinical samples related to prostate cancer (42 tissues and 110 each of urine and plasma). These unbiased metabolomic profiles were able to distinguish benign prostate, clinically localized prostate cancer and metastatic disease. Sarcosine, an N-methyl derivative of the amino acid glycine, was identified as a differential metabolite that was highly increased during prostate cancer progression to metastasis and can be detected non-invasively in urine. Sarcosine levels were also increased in invasive prostate cancer cell lines relative to benign prostate epithelial cells. Knockdown of glycine-N-methyl transferase, the enzyme that generates sarcosine from glycine, attenuated prostate cancer invasion. Addition of exogenous sarcosine or knockdown of the enzyme that leads to sarcosine degradation, sarcosine dehydrogenase, induced an invasive phenotype in benign prostate epithelial cells. Androgen receptor and the ERG gene fusion product coordinately regulate components of the sarcosine pathway. Here, by profiling the metabolomic alterations of prostate cancer progression, we reveal sarcosine as a potentially important metabolic intermediary of cancer cell invasion and aggressivity.

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Current approaches for assessing insulin sensitivity and resistance in vivo: advantages, limitations, and appropriate usage.

Ranganath Muniyappa, Sihoon Lee, Hui Chen … (2008)

Insulin resistance contributes to the pathophysiology of diabetes and is a hallmark of obesity, metabolic syndrome, and many cardiovascular diseases. Therefore, quantifying insulin sensitivity/resistance in humans and animal models is of great importance for epidemiological studies, clinical and basic science investigations, and eventual use in clinical practice. Direct and indirect methods of varying complexity are currently employed for these purposes. Some methods rely on steady-state analysis of glucose and insulin, whereas others rely on dynamic testing. Each of these methods has distinct advantages and limitations. Thus, optimal choice and employment of a specific method depends on the nature of the studies being performed. Established direct methods for measuring insulin sensitivity in vivo are relatively complex. The hyperinsulinemic euglycemic glucose clamp and the insulin suppression test directly assess insulin-mediated glucose utilization under steady-state conditions that are both labor and time intensive. A slightly less complex indirect method relies on minimal model analysis of a frequently sampled intravenous glucose tolerance test. Finally, simple surrogate indexes for insulin sensitivity/resistance are available (e.g., QUICKI, HOMA, 1/insulin, Matusda index) that are derived from blood insulin and glucose concentrations under fasting conditions (steady state) or after an oral glucose load (dynamic). In particular, the quantitative insulin sensitivity check index (QUICKI) has been validated extensively against the reference standard glucose clamp method. QUICKI is a simple, robust, accurate, reproducible method that appropriately predicts changes in insulin sensitivity after therapeutic interventions as well as the onset of diabetes. In this Frontiers article, we highlight merits, limitations, and appropriate use of current in vivo measures of insulin sensitivity/resistance.

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Retinol-binding protein 4 and insulin resistance in lean, obese, and diabetic subjects.

Timothy E Graham, Qin Yang, Matthias Blüher … (2006)

Insulin resistance has a causal role in type 2 diabetes. Serum levels of retinol-binding protein 4 (RBP4), a protein secreted by adipocytes, are increased in insulin-resistant states. Experiments in mice suggest that elevated RBP4 levels cause insulin resistance. We sought to determine whether serum RBP4 levels correlate with insulin resistance and change after an intervention that improves insulin sensitivity. We also determined whether elevated serum RBP4 levels are associated with reduced expression of glucose transporter 4 (GLUT4) in adipocytes, an early pathological feature of insulin resistance. We measured serum RBP4, insulin resistance, and components of the metabolic syndrome in three groups of subjects. Measurements were repeated after exercise training in one group. GLUT4 protein was measured in isolated adipocytes. Serum RBP4 levels correlated with the magnitude of insulin resistance in subjects with obesity, impaired glucose tolerance, or type 2 diabetes and in nonobese, nondiabetic subjects with a strong family history of type 2 diabetes. Elevated serum RBP4 was associated with components of the metabolic syndrome, including increased body-mass index, waist-to-hip ratio, serum triglyceride levels, and systolic blood pressure and decreased high-density lipoprotein cholesterol levels. Exercise training was associated with a reduction in serum RBP4 levels only in subjects in whom insulin resistance improved. Adipocyte GLUT4 protein and serum RBP4 levels were inversely correlated. RBP4 is an adipocyte-secreted molecule that is elevated in the serum before the development of frank diabetes and appears to identify insulin resistance and associated cardiovascular risk factors in subjects with varied clinical presentations. These findings provide a rationale for antidiabetic therapies aimed at lowering serum RBP4 levels. Copyright 2006 Massachusetts Medical Society.

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Author and article information

Contributors

: Role: Editor

Journal

Journal ID (nlm-ta): PLoS One

Journal ID (publisher-id): plos

Journal ID (pmc): plosone

Title: PLoS ONE

Publisher: Public Library of Science (San Francisco, USA )

ISSN (Electronic): 1932-6203

Publication date Collection: 2010

Publication date (Electronic): 28 May 2010

Volume: 5

Issue: 5

Electronic Location Identifier: e10883

Affiliations

[1 ]Metabolon, Inc., Research Triangle Park, North Carolina, United States of America

[2 ]RISC (Relationship of Insulin Sensitivity to Cardiovascular Disease) Coordinating Office, Department of Internal Medicine, University of Pisa School of Medicine, Pisa, Italy

University of Tor Vergata, Italy

Author notes

* E-mail: wgall@ 123456metabolon.com

Conceived and designed the experiments: WGPD EFMD. Performed the experiments: KPAPD. Analyzed the data: WGPD KBPD KALPD KPAPD MWMPD PJNPD JARPD MVMPD ANMD EFMD. Contributed reagents/materials/analysis tools: KPAPD MWMPD MNMD SC ANMD EFMD. Wrote the paper: WGPD KBPD KALPD KPAPD MWMPD PJNPD EFMD.

[¤]

A complete list of RISC Study Group investigators can be found in supplementary appendix ( Appendix S1).

Article

Publisher ID: 10-PONE-RA-16578R1

DOI: 10.1371/journal.pone.0010883

PMC ID: 2878333

PubMed ID: 20526369

SO-VID: 744499e5-479f-4208-b921-bec693ffd662

Copyright © Gall et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

History

Date received : 25 February 2010

Date accepted : 14 April 2010

Page count

Pages: 11

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