OBJECTIVE: The objective of the present analysis was to evaluate the association of alanine aminotransferase (ALT) with directly measured insulin sensitivity (S(i)) in a large, multiethnic cohort of U.S. adults and to determine whether ALT adds to existing metabolic risk definitions in identifying subjects with insulin resistance. RESEARCH DESIGN AND METHODS: S(i) was directly measured from frequently sampled intravenous glucose tolerance tests among 999 nondiabetic African-American, Hispanic, and non-Hispanic white subjects aged 40-69 years who were participating in the Insulin Resistance Atherosclerosis Study. Subjects also received an oral glucose tolerance test, and fasting insulin, ALT, and alcohol intake were determined. RESULTS: ALT was associated with S(i) after adjustment for age, sex, ethnicity, impaired fasting glucose, triglycerides, HDL, blood pressure, and waist (clinical model) (P < 0.0001). The association remained significant after further adjustment for fasting insulin and impaired glucose tolerance (P = 0.004). In logistic regression analysis, elevated ALT (upper quartile) was associated with insulin resistance (lowest quartile of S(i)) after adjustment for age, sex, and ethnicity (odds ratio 3.0 [95% CI 2.2-4.1]). Elevated ALT was independently associated with insulin resistance when included in models with waist circumference, National Cholesterol Education Program criteria for metabolic syndrome, hypertriglyceridemic waist, elevated triglyceride-to-HDL ratio, or homeostasis model assessment of insulin resistance (HOMA-IR) (all P < 0.01). Finally, the addition of elevated ALT improved classification of insulin resistance by area under the receiver operating characteristic curve criteria for all models except HOMA-IR. CONCLUSIONS: ALT was associated with insulin resistance independently of conventional and more detailed metabolic measures. These findings suggest that the addition of ALT to existing clinically based metabolic risk definitions is an inexpensive way to improve the identification of subjects with insulin resistance.
OBJECTIVE: The objective of the present analysis was to evaluate the association of alanine aminotransferase (ALT) with directly measured insulin sensitivity (S(i)) in a large, multiethnic cohort of U.S. adults and to determine whether ALT adds to existing metabolic risk definitions in identifying subjects with insulin resistance. RESEARCH DESIGN AND METHODS: S(i) was directly measured from frequently sampled intravenous glucose tolerance tests among 999 nondiabetic African-American, Hispanic, and non-Hispanic white subjects aged 40-69 years who were participating in the Insulin Resistance Atherosclerosis Study. Subjects also received an oral glucose tolerance test, and fasting insulin, ALT, and alcohol intake were determined. RESULTS: ALT was associated with S(i) after adjustment for age, sex, ethnicity, impaired fasting glucose, triglycerides, HDL, blood pressure, and waist (clinical model) (P < 0.0001). The association remained significant after further adjustment for fasting insulin and impaired glucose tolerance (P = 0.004). In logistic regression analysis, elevated ALT (upper quartile) was associated with insulin resistance (lowest quartile of S(i)) after adjustment for age, sex, and ethnicity (odds ratio 3.0 [95% CI 2.2-4.1]). Elevated ALT was independently associated with insulin resistance when included in models with waist circumference, National Cholesterol Education Program criteria for metabolic syndrome, hypertriglyceridemic waist, elevated triglyceride-to-HDL ratio, or homeostasis model assessment of insulin resistance (HOMA-IR) (all P < 0.01). Finally, the addition of elevated ALT improved classification of insulin resistance by area under the receiver operating characteristic curve criteria for all models except HOMA-IR. CONCLUSIONS: ALT was associated with insulin resistance independently of conventional and more detailed metabolic measures. These findings suggest that the addition of ALT to existing clinically based metabolic risk definitions is an inexpensive way to improve the identification of subjects with insulin resistance.
Authors: Blaire E Burman; Peter Bacchetti; Claudia E Ayala; Nicholas Gelman; Jennifer Melgar; Mandana Khalili Journal: Liver Int Date: 2014-09-20 Impact factor: 5.828
Authors: Amalia Gastaldelli; Lucia Perego; Michele Paganelli; Giorgio Sesti; Marta Hribal; Alberto O Chavez; Ralph A Defronzo; Antonio Pontiroli; Franco Folli Journal: Obes Surg Date: 2008-09-24 Impact factor: 4.129
Authors: Gábor Firneisz; Tímea Varga; Gabriella Lengyel; János Fehér; Dóra Ghyczy; Barna Wichmann; László Selmeci; Zsolt Tulassay; Károly Rácz; Anikó Somogyi Journal: PLoS One Date: 2010-08-18 Impact factor: 3.240