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Quantifying the improvement of surrogate indices of hepatic insulin resistance using complex measurement techniques
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Hattersley, John G., Möhlig, Matthias, Roden, Michael, Dr., Arafat, Ayman M., Loeffelholz, Christian von, Nowotny, Peter, Machann, Jürgen, Hierholzer, Johannes, Osterhoff, Martin, Khan, Michael, Pfeiffer, Andreas F. H. and Weickert, Martin O. (2012) Quantifying the improvement of surrogate indices of hepatic insulin resistance using complex measurement techniques. PLoS ONE, Vol.7 (No.6). Article no. e39029. doi:10.1371/journal.pone.0039029 ISSN 1932-6203.
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Official URL: http://dx.doi.org/10.1371/journal.pone.0039029
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/m2; 30 males). HEP-IR was defined by measuring endogenous-glucose-production (EGP) with [6–62H2] 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 (r2 = 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.
Item Type: | Journal Article | ||||
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Subjects: | Q Science > QA Mathematics R Medicine > R Medicine (General) |
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Divisions: | Faculty of Science, Engineering and Medicine > Medicine > Warwick Medical School | ||||
Library of Congress Subject Headings (LCSH): | Insulin resistance -- Diagnosis, Epidemiology -- Statistical methods | ||||
Journal or Publication Title: | PLoS ONE | ||||
Publisher: | PLOS | ||||
ISSN: | 1932-6203 | ||||
Official Date: | 2012 | ||||
Dates: |
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Volume: | Vol.7 | ||||
Number: | No.6 | ||||
Page Range: | Article no. e39029 | ||||
DOI: | 10.1371/journal.pone.0039029 | ||||
Status: | Peer Reviewed | ||||
Publication Status: | Published | ||||
Access rights to Published version: | Open Access (Creative Commons) | ||||
Date of first compliant deposit: | 22 December 2015 | ||||
Date of first compliant Open Access: | 22 December 2015 | ||||
Funder: | Germany. Bundesministerium für Bildung und Forschung (BMBF) | ||||
Grant number: | 0313826A (BMBF) |
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