Lipoprotein insulin resistance index, a high-throughput measure of insulin resistance, is associated with incident type II diabetes mellitus in the Prevention of Renal and Vascular End-Stage Disease study

Jose L Flores-Guerrero; Margery A Connelly; Irina Shalaurova; Eke G Gruppen; Lyanne M Kieneker; Robin P F Dullaart; Stephan J L Bakker

doi:10.1016/j.jacl.2018.11.009

Lipoprotein insulin resistance index, a high-throughput measure of insulin resistance, is associated with incident type II diabetes mellitus in the Prevention of Renal and Vascular End-Stage Disease study

J Clin Lipidol. 2019 Jan-Feb;13(1):129-137.e1. doi: 10.1016/j.jacl.2018.11.009. Epub 2018 Dec 1.

Authors

Jose L Flores-Guerrero¹, Margery A Connelly², Irina Shalaurova², Eke G Gruppen³, Lyanne M Kieneker³, Robin P F Dullaart⁴, Stephan J L Bakker³

Affiliations

¹ Department of Nephrology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands. Electronic address: j.l.flores.guerrero@umcg.nl.
² Laboratory Corporation of America Holdings (LabCorp), Morrisville, NC, USA.
³ Department of Nephrology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands.
⁴ Department of Endocrinology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands.

PMID: 30591414
DOI: 10.1016/j.jacl.2018.11.009

Abstract

Background: Early assessment of insulin resistance may be a way of identifying patients at risk as well as monitoring treatments that increase insulin sensitivity and reduce the risk of developing type II diabetes mellitus (T2DM).

Objective: The objective of the study was to evaluate the ability of the Lipoprotein Insulin Resistance Index (LP-IR) to predict incident T2DM in a large cohort.

Methods: LP-IR scores were calculated using 6 lipoprotein particle concentrations and sizes measured by nuclear magnetic resonance spectroscopy. In total, 5977 nondiabetic men and women were included. Cox proportional hazards regression was used to evaluate the association of LP-IR scores with incident T2DM.

Results: LP-IR scores were closely associated with insulin resistance, assessed by homeostatic model assessment of insulin resistance (r = 0.51; P < .0001). During a median follow-up for 7.5 years, 278 new T2DM cases were ascertained. The Kaplan-Meier plot with log-rank test (P < .001) demonstrated that elevated LP-IR levels are associated with an increased T2DM risk. In analyses adjusted for age and sex, LP-IR was associated with incident T2DM; hazard ratio (HR) for the highest versus lowest quartile was 10.18 (95% confidence interval: 6.24-16.61), P < .0001. After adjustment for clinical risk factors, the HR was attenuated but remained significant (HR 3.02 [1.73-5.25], P < .0001). LP-IR scores added significantly to the performance of the Framingham Offspring prediction algorithm; C-index (95% confidence interval) for the Framingham Offspring score without and with LP-IR (0.863 [0.863-0.864] and 0.868 [0.867-0.86], P < .0001). Similar results were observed when LP-IR was analyzed as a categorical variable with a clinical cut-point of 68.

Conclusion: LP-IR may be a convenient way to assess insulin resistance and T2DM risk, as well as to monitor preventative treatments.

Keywords: Diabetes prevention; Insulin resistance; LP-IR; Lipoproteins; Risk prediction; Type II diabetes mellitus.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Adult
Aged
Cohort Studies
Diabetes Mellitus, Type 2 / epidemiology*
Diabetes Mellitus, Type 2 / mortality
Diabetic Angiopathies / epidemiology*
Diabetic Angiopathies / mortality
Female
Follow-Up Studies
High-Throughput Screening Assays
Humans
Incidence
Insulin Resistance / physiology*
Kidney Failure, Chronic / epidemiology*
Lipoproteins / metabolism*
Male
Middle Aged
Models, Statistical
Netherlands / epidemiology
Prognosis
Risk
Survival Analysis

Substances

Lipoproteins