title: Quantifying the improvement of surrogate indices of hepatic insulin resistance using complex measurement techniques.
abstract: We evaluated the ability of simple and complex surrogate-indices to identify individuals from an overweight/obese cohort with hepatic insulin-resistance (HEP-IR). Five indices, one previously defined and four newly generated through step-wise linear regression, were created against a single-cohort sample of 77 extensively characterised participants with the metabolic syndrome (age 55.6 ± 1.0 years, BMI 31.5 ± 0.4 kg/m(2); 30 males). HEP-IR was defined by measuring endogenous-glucose-production (EGP) with [6-6(2)H(2)] glucose during fasting and euglycemic-hyperinsulinemic clamps and expressed as EGP*fasting plasma insulin. Complex measures were incorporated into the model, including various non-standard biomarkers and the measurement of body-fat distribution and liver-fat, to further improve the predictive capability of the index. Validation was performed against a data set of the same subjects after an isoenergetic dietary intervention (4 arms, diets varying in protein and fiber content versus control). All five indices produced comparable prediction of HEP-IR, explaining 39-56% of the variance, depending on regression variable combination. The validation of the regression equations showed little variation between the different proposed indices (r(2) = 27-32%) on a matched dataset. New complex indices encompassing advanced measurement techniques offered an improved correlation (r = 0.75, P<0.001). However, when validated against the alternative dataset all indices performed comparably with the standard homeostasis model assessment for insulin resistance (HOMA-IR) (r = 0.54, P<0.001). Thus, simple estimates of HEP-IR performed comparable to more complex indices and could be an efficient and cost effective approach in large epidemiological investigations.
authors: Warwickshire Institute for the Study of Diabetes, Endocrinology and Metabolism, University Hospitals Coventry and Warwickshire NHS Trust, Coventry, United Kingdom.
authors: John G
authors: JG
authors: Hattersley
authors: Matthias
authors: M
authors: Möhlig
authors: Michael
authors: M
authors: Roden
authors: Ayman M
authors: AM
authors: Arafat
authors: Christian V
authors: CV
authors: Loeffelholz
authors: Peter
authors: P
authors: Nowotny
authors: Jürgen
authors: J
authors: Machann
authors: Johannes
authors: J
authors: Hierholzer
authors: Martin
authors: M
authors: Osterhoff
authors: Michael
authors: M
authors: Khan
authors: Andreas F H
authors: AF
authors: Pfeiffer
authors: Martin O
authors: MO
authors: Weickert
mesh_terms: D015415:Biomarkers / Q000097:blood*; D001786:Blood Glucose / Q000378:metabolism; D015992:Body Mass Index; D005215:Fasting / Q000502:physiology; D005260:Female; D015309:Glucose Clamp Technique; D005951:Glucose Tolerance Test; D006801:Humans; D007328:Insulin / Q000378:metabolism; D007333:Insulin Resistance; D008099:Liver / Q000378:metabolism*; D008137:Longitudinal Studies; D008297:Male; D024821:Metabolic Syndrome / Q000503:physiopathology*; D008875:Middle Aged; D009765:Obesity / Q000503:physiopathology*; D050177:Overweight / Q000503:physiopathology*
chemical_list: D015415:Biomarkers; D001786:Blood Glucose; D007328:Insulin