Cited by 259Diabetes, Cardiovascular Risks, and LipoproteinsPancreatic function and diabetesAdipokines, Inflammation, and Metabolic Diseases

Incorporation of the Fasting Plasma FFA Concentration into QUICKI Improves Its Association with Insulin Sensitivity in Nonobese Individuals

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Perseghin, Gianluca, Caumo, Andrea, Caloni, Marianna, Testolin, Giulio, Luzi, Livio·2001·The Journal of Clinical Endocrinology & Metabolism

Abstract

Insulin resistance plays a major role in the pathophysiology of diabetes and is associated with obesity and cardiovascular disease. Excellent methods exist for the assessment of insulin sensitivity in the laboratory setting, such as the glucose clamp. However, these methods are not suitable for large population studies, and, thus, surrogate estimates of insulin sensitivity based on measurements in a single blood sample have been developed. Recently an index based on the logarithm and the reciprocal of the insulin-glucose product (QUICKI) has been proposed. QUICKI correlated with insulin sensitivity across the entire spectrum of glucose tolerance, but its performance was less satisfactory in normal subjects. Aim of this study was to ascertain whether the inclusion of fasting plasma free fatty acids concentration into QUICKI improves its association with insulin sensitivity in nonobese subjects. To test this hypothesis, we performed a euglycemic hyperinsulinemic clamp [40 mU/(m(2).min)] in 57 young, healthy, nonobese individuals with (n = 17) or without (n = 40) first-degree relatives affected by type 2 diabetes (the former group being an in vivo model of mild insulin resistance). We then compared the clamp-based index of insulin sensitivity with both QUICKI and a revised QUICKI, the latter index including the contribution of fasting free fatty acid concentration as well. The revised QUICKI considerably improved the relationship with the clamp-based index of insulin sensitivity (r = 0.51, P < 0.0001) with respect to QUICKI (r = 0.27, P < 0.05). In addition, the revised QUICKI revealed a reduction of insulin sensitivity in the offspring of type 2 diabetes (10%; P < 0.006) that QUICKI was unable to detect (3%; P = 0.28). In conclusion, this study suggests that the incorporation of fasting free fatty acid level into QUICKI is useful to improve its correlation with the clamp-based index of insulin sensitivity and its discriminatory power in case of mild insulin resistance. Further investigation is needed to ascertain its applicability to patients with obesity and type 2 diabetes.

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Crossref · 10.1210/jcem.86.10.7902

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Authors
Perseghin, G., Caumo, A., Caloni, M., Testolin, G., & Luzi, L.
Affiliations
  • University of Milan (IT)
  • Biometrical Unit (A.C.), Milan, Italy 20132
  • Vita-Salute San Raffaele University (IT)
Corresponding author
Perseghin, Gianluca
Venue
The Journal of Clinical Endocrinology & Metabolism
Published
2001-10-01
Volume
86
Issue
10
Pages
4776-4781
ISSN
  • 0021-972X (ISSN-L)
  • 1945-7197
OpenAlex
W2096345851
Cited by
259
References
7
Citations by year
2026: 5 · 2025: 4 · 2024: 5 · 2023: 9 · 2022: 11 · 2021: 10 · 2020: 9 · 2019: 14 · 2018: 7 · 2017: 17 · 2016: 15 · 2015: 11 · 2014: 9 · 2013: 8 · 2012: 14
FWCI
5.87
Type
journal article
Language
en
Open access
Locations
  • The Journal of Clinical Endocrinology & Metabolism (publishedVersion)
  • PubMed (publishedVersion)
  • Archivio Istituzionale della Ricerca (Universita Degli Studi Di Milano) (submittedVersion, other-oa)
  • BOA (University of Milano-Bicocca) (submittedVersion)
Topics
  • Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes, Cardiovascular Risks, and Lipoproteins
  • Health Sciences › Medicine › Surgery › Pancreatic function and diabetes
  • Health Sciences › Medicine › Epidemiology › Adipokines, Inflammation, and Metabolic Diseases
Keywords
QUICKI, insulin sensitivity, insulin resistance, type 2 diabetes, first-degree relatives, hyperinsulinemic-euglycemic clamp
MeSH terms
Adult, Diabetes Mellitus, Type 2, Fatty Acids, Nonesterified, Humans, Insulin, Insulin Resistance, Lipolysis, Middle Aged, Regression Analysis

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