Novel Proteome Targets Marking Insulin Resistance in Metabolic Syndrome

Author:

Warmbrunn Moritz V.123ORCID,Bahrar Harsh4ORCID,de Clercq Nicolien C.1,Koopen Annefleur M.1,de Groot Pieter F.1,Rutten Joost4,Joosten Leo A. B.4ORCID,Kootte Ruud S.1,Bouter Kristien E. C.1,ter Horst Kasper W.1,Hartstra Annick V.1,Serlie Mireille J.5,Soeters Maarten R.5,van Raalte Daniel H.67,Davids Mark1ORCID,Levin Evgeni1,Herrema Hilde1,Riksen Niels P.4ORCID,Netea Mihai G.4,Groen Albert K.1,Nieuwdorp Max1

Affiliation:

1. Department of Internal and Vascular Medicine, Amsterdam University Medical Centers, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands

2. Amsterdam UMC, Gastroenterology and Hepatology, Amsterdam Gastroenterology Endocrinology Metabolism, University of Amsterdam, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands

3. Amsterdam UMC, Cardiovascular Sciences, Amsterdam Cardiovascular Sciences, University of Amsterdam, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands

4. Department of Internal Medicine, Radboud University Medical Center, 6525 EP Nijmegen, The Netherlands

5. Department of Endocrinology and Metabolism, Amsterdam UMC, University of Amsterdam, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands

6. Diabetes Center, Department of Endocrniology and Metabolism, Amsterdam UMC, VU University Medical Centers, De Boelelaan 1117, 1081 HV Amsterdam, The Netherlands

7. Amsterdam Cardiovascular Sciences, VU University, De Boelelaan 1117, 1081 HV Amsterdam, The Netherlands

Abstract

Context/Objective: In order to better understand which metabolic differences are related to insulin resistance in metabolic syndrome (MetSyn), we used hyperinsulinemic–euglycemic (HE) clamps in individuals with MetSyn and related peripheral insulin resistance to circulating biomarkers. Design/Methods: In this cross-sectional study, HE-clamps were performed in treatment-naive men (n = 97) with MetSyn. Subjects were defined as insulin-resistant based on the rate of disappearance (Rd). Machine learning models and conventional statistics were used to identify biomarkers of insulin resistance. Findings were replicated in a cohort with n = 282 obese men and women with (n = 156) and without (n = 126) MetSyn. In addition to this, the relation between biomarkers and adipose tissue was assessed by nuclear magnetic resonance imaging. Results: Peripheral insulin resistance is marked by changes in proteins related to inflammatory processes such as IL-1 and TNF-receptor and superfamily members. These proteins can distinguish between insulin-resistant and insulin-sensitive individuals (AUC = 0.72 ± 0.10) with MetSyn. These proteins were also associated with IFG, liver fat (rho 0.36, p = 1.79 × 10−9) and visceral adipose tissue (rho = 0.35, p = 6.80 × 10−9). Interestingly, these proteins had the strongest association in the MetSyn subgroup compared to individuals without MetSyn. Conclusions: MetSyn associated with insulin resistance is characterized by protein changes related to body fat content, insulin signaling and pro-inflammatory processes. These findings provide novel targets for intervention studies and should be the focus of future in vitro and in vivo studies.

Funder

Netherlands CardioVascular Research Committee (CVON) IN-CONTROL-II) grant from the Dutch Heart Foundation and Dutch Cardiovascular Alliance

ZonMw Vici grant 2020

Leducq consortium

Senior Fellowship of the Dutch Diabetes Research Foundation

Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)—SFB 1454

Publisher

MDPI AG

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