Intact Fasting Insulin Identifies Nonalcoholic Fatty Liver Disease in Patients Without Diabetes.


Journal

The Journal of clinical endocrinology and metabolism
ISSN: 1945-7197
Titre abrégé: J Clin Endocrinol Metab
Pays: United States
ID NLM: 0375362

Informations de publication

Date de publication:
21 10 2021
Historique:
received: 30 03 2021
pubmed: 1 7 2021
medline: 15 12 2021
entrez: 30 6 2021
Statut: ppublish

Résumé

Patients with nonalcoholic fatty liver disease (NAFLD) are characterized by insulin resistance and hyperinsulinism. However, insulin resistance measurements have not been shown to be good diagnostic tools to predict NAFLD in prior studies. We aimed to assess a newly validated method to measure intact molecules of insulin by mass spectrometry to predict NAFLD. Patients underwent a 2-hour oral glucose tolerance test (OGTT), a liver magnetic resonance spectroscopy (1H-MRS), and a percutaneous liver biopsy if they had a diagnosis of NAFLD. Mass spectrometry was used to measure intact molecules of insulin and C-peptide. A total of 180 patients were recruited (67% male; 52 ± 11 years of age; body mass index [BMI] 33.2 ± 5.7 kg/m2; 46% with diabetes and 65% with NAFLD). Intact fasting insulin was higher in patients with NAFLD, irrespective of diabetes status. Patients with NAFLD without diabetes showed ~4-fold increase in insulin secretion during the OGTT compared with all other subgroups (P = 0.008). Fasting intact insulin measurements predicted NAFLD in patients without diabetes (area under the receiver operating characteristic curve [AUC] of 0.90 [0.84-0.96]). This was significantly better than measuring insulin by radioimmunoassay (AUC 0.80 [0.71-0.89]; P = 0.007). Intact fasting insulin was better than other clinical variables (eg, aspartate transaminase, triglycerides, high-density lipoprotein, glucose, HbA1c, and BMI) to predict NAFLD. When combined with alanine transaminase (ALT) (intact insulin × ALT), it detected NAFLD with AUC 0.94 (0.89-0.99) and positive and negative predictive values of 93% and 88%, respectively. This newly described approach was significantly better than previously validated noninvasive scores such as NAFLD-LFS (P = 0.009), HSI (P < 0.001), and TyG index (P = 0.039). In patients without diabetes, accurate measurement of fasting intact insulin levels by mass spectrometry constitutes an easy and noninvasive strategy to predict presence of NAFLD.

Identifiants

pubmed: 34190318
pii: 6311619
doi: 10.1210/clinem/dgab417
doi:

Substances chimiques

C-Peptide 0
Insulin 0
Alanine Transaminase EC 2.6.1.2

Types de publication

Comparative Study Journal Article Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S.

Langues

eng

Sous-ensembles de citation

IM

Pagination

e4360-e4371

Subventions

Organisme : VA
ID : 1 I01 CX000167-01
Pays : United States

Informations de copyright

© The Author(s) 2021. Published by Oxford University Press on behalf of the Endocrine Society. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Auteurs

Fernando Bril (F)

Internal Medicine, Department of Medicine, University of Alabama at Birmingham, Birmingham, AL 35294, USA.
Division of Endocrinology, Diabetes and Metabolism, University of Florida, Gainesville, FL 32610, USA.

Michael J McPhaul (MJ)

Quest Diagnostics Nichols Institute, San Juan Capistrano, CA 92675, USA.

Srilaxmi Kalavalapalli (S)

Division of Endocrinology, Diabetes and Metabolism, University of Florida, Gainesville, FL 32610, USA.

Romina Lomonaco (R)

Division of Endocrinology, Diabetes and Metabolism, University of Florida, Gainesville, FL 32610, USA.

Diana Barb (D)

Division of Endocrinology, Diabetes and Metabolism, University of Florida, Gainesville, FL 32610, USA.

Meagan E Gray (ME)

Division of Gastroenterology, Hepatology and Nutrition, University of Alabama at Birmingham, Birmingham, AL 35294, USA.

Dov Shiffman (D)

Quest Diagnostics Nichols Institute, San Juan Capistrano, CA 92675, USA.

Charles M Rowland (CM)

Quest Diagnostics Nichols Institute, San Juan Capistrano, CA 92675, USA.

Kenneth Cusi (K)

Division of Endocrinology, Diabetes and Metabolism, University of Florida, Gainesville, FL 32610, USA.
Division of Endocrinology, Diabetes and Metabolism, Malcom Randall, VAMC, Gainesville, FL 32611, USA.

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Classifications MeSH