Acta Diabetologica

, Volume 51, Issue 1, pp 123–131 | Cite as

The inflammatory status score including IL-6, TNF-α, osteopontin, fractalkine, MCP-1 and adiponectin underlies whole-body insulin resistance and hyperglycemia in type 2 diabetes mellitus

  • G. Daniele
  • R. Guardado Mendoza
  • D. Winnier
  • T. V. Fiorentino
  • Z. Pengou
  • J. Cornell
  • F. Andreozzi
  • C. Jenkinson
  • E. Cersosimo
  • M. Federici
  • D. Tripathy
  • F. FolliEmail author
Original Article


A state of subclinical systemic inflammation is characteristically present in obesity/insulin resistance and type 2 diabetes mellitus (T2DM). The aim of the study was to develop an integrated measure of the circulating cytokines involved in the subclinical systemic inflammation and evaluate its relation with whole-body insulin sensitivity and glucose metabolism in T2DM. T2DM patients (n = 17, M/F 13/4, age = 55.0 ± 1.7 years, BMI = 33.5 ± 1.5 kg/m2, HbA1c = 7.7 ± 0.3 %) and normal glucose-tolerant (NGT) subjects (n = 15, M/F 7/8, age = 49.1 ± 2.5 years, BMI = 31.8 ± 1.2 kg/m2, HbA1c = 5.6 ± 0.1 %) were studied in a cross-sectional design. Whole-body insulin sensitivity was quantified by the euglycemic clamp. Beta-cell function [disposition index (DI)] was calculated using insulin and glucose values derived from an oral glucose tolerance test and the euglycemic clamp. Body fat mass was evaluated by dual-energy X-ray absorptiometry. Plasma cytokine [TNF-α, IL-6, MCP-1, osteopontin, fractalkine and adiponectin] values were divided into quintiles. A score ranging from 0 (lowest quintile) to 4 (highest quintile) was assigned. The inflammatory score (IS) was the sum of each cytokine score from which adiponectin score was subtracted in each study subject. Inflammatory cytokine levels were all higher in T2DM. IS was higher in T2DM as compared to NGT (10.0 ± 1.1 vs. 4.8 ± 0.8; p < 0.001). IS positively correlated with fasting plasma glucose (r = 0.638, p < 0.001), 1-h plasma glucose (r = 0.483, p = 0.005), 2-h plasma glucose (r = 0.611, p < 0.001) and HbA1c (r = 0.469, p = 0.007). IS was inversely correlated with insulin sensitivity (r = −0.478, p = 0.006) and DI (r = −0.523, p = 0.002). IS did not correlate with BMI and body fat mass. IS was an independent predictor of fasting plasma glucose and had a high sensibility and sensitivity to predict insulin resistance (M/I < 4). A state of subclinical inflammation defined and quantifiable by inflammatory score including TNF-α, IL-6, MCP-1, osteopontin, fractalkine and adiponectin is associated with both hyperglycemia and whole-body insulin resistance in T2DM.


Type 2 diabetes mellitus Inflammation IL-6 TNF-α Fractalkine MCP-1 Adiponectin Osteopontin Glucose metabolism Euglycemic hyperinsulinemic clamp Whole-body insulin sensitivity Disposition index 



Type 2 diabetes mellitus


Inflammatory score


Dual-energy X-ray absorptiometry


Fasting plasma glucose


Oral Glucose Tolerance Test


Plasma glucose

1 h PG

1-Hour plasma glucose

2 h PG

2-Hour plasma glucose




Monocyte chemoattractant protein-1


Tumor necrosis factor-α








Insulin resistance



This work was presented in part in abstract form at the Endocrine Society Meeting, 2013, in San Francisco, CA, USA. G. D. was supported in part by a fellowship from Fo.Ri.SID, Italy.

Conflict of interest


Supplementary material

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Supplementary material 1 (PPTX 48 kb)
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Supplementary material 6 (PPTX 169 kb)


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Copyright information

© Springer-Verlag Italia 2013

Authors and Affiliations

  • G. Daniele
    • 1
  • R. Guardado Mendoza
    • 1
    • 2
  • D. Winnier
    • 1
  • T. V. Fiorentino
    • 1
    • 3
  • Z. Pengou
    • 1
  • J. Cornell
    • 4
  • F. Andreozzi
    • 1
    • 3
  • C. Jenkinson
    • 1
  • E. Cersosimo
    • 1
  • M. Federici
    • 5
  • D. Tripathy
    • 1
  • F. Folli
    • 1
    Email author
  1. 1.Division of Diabetes, Department of MedicineUniversity of Texas Health Science Center at San AntonioSan AntonioUSA
  2. 2.Division of Health Sciences, Department of Medicine and Nutrition, Campus LeònUniversity of GuanajuatoLeònMexico
  3. 3.Department of Medical and Surgical SciencesUniversity “Magna Graecia” of CatanzaroCatanzaroItaly
  4. 4.Department of Epidemiology and BiostatisticUniversity of Texas Health Science CenterSan AntonioUSA
  5. 5.Department of Internal MedicineUniversity of Tor VergataRomeItaly

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