Predictors of Whole-Body Insulin Sensitivity Across Ages and Adiposity in Adult Humans.

Autor:	Lalia AZ; Divisions of Endocrinology and Metabolism (A.Z.L., M.L.J., M.M.R., A.R.K., K.D., R.R.E., K.S.N., I.R.L.), Biomedical Statistics and Informatics (S.D.), and Radiology (J.D.P., M.T.G.), Mayo Clinic College of Medicine, Rochester, Minnesota 55905., Dasari S; Divisions of Endocrinology and Metabolism (A.Z.L., M.L.J., M.M.R., A.R.K., K.D., R.R.E., K.S.N., I.R.L.), Biomedical Statistics and Informatics (S.D.), and Radiology (J.D.P., M.T.G.), Mayo Clinic College of Medicine, Rochester, Minnesota 55905., Johnson ML; Divisions of Endocrinology and Metabolism (A.Z.L., M.L.J., M.M.R., A.R.K., K.D., R.R.E., K.S.N., I.R.L.), Biomedical Statistics and Informatics (S.D.), and Radiology (J.D.P., M.T.G.), Mayo Clinic College of Medicine, Rochester, Minnesota 55905., Robinson MM; Divisions of Endocrinology and Metabolism (A.Z.L., M.L.J., M.M.R., A.R.K., K.D., R.R.E., K.S.N., I.R.L.), Biomedical Statistics and Informatics (S.D.), and Radiology (J.D.P., M.T.G.), Mayo Clinic College of Medicine, Rochester, Minnesota 55905., Konopka AR; Divisions of Endocrinology and Metabolism (A.Z.L., M.L.J., M.M.R., A.R.K., K.D., R.R.E., K.S.N., I.R.L.), Biomedical Statistics and Informatics (S.D.), and Radiology (J.D.P., M.T.G.), Mayo Clinic College of Medicine, Rochester, Minnesota 55905., Distelmaier K; Divisions of Endocrinology and Metabolism (A.Z.L., M.L.J., M.M.R., A.R.K., K.D., R.R.E., K.S.N., I.R.L.), Biomedical Statistics and Informatics (S.D.), and Radiology (J.D.P., M.T.G.), Mayo Clinic College of Medicine, Rochester, Minnesota 55905., Port JD; Divisions of Endocrinology and Metabolism (A.Z.L., M.L.J., M.M.R., A.R.K., K.D., R.R.E., K.S.N., I.R.L.), Biomedical Statistics and Informatics (S.D.), and Radiology (J.D.P., M.T.G.), Mayo Clinic College of Medicine, Rochester, Minnesota 55905., Glavin MT; Divisions of Endocrinology and Metabolism (A.Z.L., M.L.J., M.M.R., A.R.K., K.D., R.R.E., K.S.N., I.R.L.), Biomedical Statistics and Informatics (S.D.), and Radiology (J.D.P., M.T.G.), Mayo Clinic College of Medicine, Rochester, Minnesota 55905., Esponda RR; Divisions of Endocrinology and Metabolism (A.Z.L., M.L.J., M.M.R., A.R.K., K.D., R.R.E., K.S.N., I.R.L.), Biomedical Statistics and Informatics (S.D.), and Radiology (J.D.P., M.T.G.), Mayo Clinic College of Medicine, Rochester, Minnesota 55905., Nair KS; Divisions of Endocrinology and Metabolism (A.Z.L., M.L.J., M.M.R., A.R.K., K.D., R.R.E., K.S.N., I.R.L.), Biomedical Statistics and Informatics (S.D.), and Radiology (J.D.P., M.T.G.), Mayo Clinic College of Medicine, Rochester, Minnesota 55905., Lanza IR; Divisions of Endocrinology and Metabolism (A.Z.L., M.L.J., M.M.R., A.R.K., K.D., R.R.E., K.S.N., I.R.L.), Biomedical Statistics and Informatics (S.D.), and Radiology (J.D.P., M.T.G.), Mayo Clinic College of Medicine, Rochester, Minnesota 55905.
Jazyk:	angličtina
Zdroj:	The Journal of clinical endocrinology and metabolism [J Clin Endocrinol Metab] 2016 Feb; Vol. 101 (2), pp. 626-34. Date of Electronic Publication: 2015 Dec 28.
DOI:	10.1210/jc.2015-2892
Abstrakt:	Context: Numerous factors are purported to influence insulin sensitivity including age, adiposity, mitochondrial function, and physical fitness. Univariate associations cannot address the complexity of insulin resistance or the interrelationship among potential determinants. Objective: The objective of the study was to identify significant independent predictors of insulin sensitivity across a range of age and adiposity in humans. Design, Setting, and Participants: Peripheral and hepatic insulin sensitivity were measured by two stage hyperinsulinemic-euglycemic clamps in 116 men and women (aged 19-78 y). Insulin-stimulated glucose disposal, the suppression of endogenous glucose production during hyperinsulinemia, and homeostatic model assessment of insulin resistance were tested for associations with 11 potential predictors. Abdominal subcutaneous fat, visceral fat (AFVISC), intrahepatic lipid, and intramyocellular lipid (IMCL) were quantified by magnetic resonance imaging and spectroscopy. Skeletal muscle mitochondrial respiratory capacity (state 3), coupling efficiency, and reactive oxygen species production were evaluated from muscle biopsies. Aerobic fitness was measured from whole-body maximum oxygen uptake (VO2 peak), and metabolic flexibility was determined using indirect calorimetry. Results: Multiple regression analysis revealed that AFVISC (P < .0001) and intrahepatic lipid (P = .002) were independent negative predictors of peripheral insulin sensitivity, whereas VO2 peak (P = .0007) and IMCL (P = .023) were positive predictors. Mitochondrial capacity and efficiency were not independent determinants of peripheral insulin sensitivity. The suppression of endogenous glucose production during hyperinsulinemia model of hepatic insulin sensitivity revealed percentage fat (P < .0001) and AFVISC (P = .001) as significant negative predictors. Modeling homeostatic model assessment of insulin resistance identified AFVISC (P < .0001), VO2 peak (P = .001), and IMCL (P = .01) as independent predictors. Conclusion: The reduction in insulin sensitivity observed with aging is driven primarily by age-related changes in the content and distribution of adipose tissue and is independent of muscle mitochondrial function or chronological age.
Databáze:	MEDLINE
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