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Published on: June 15, 2013
Epidemiology of the insulin-like growth factor system in three ethnic groups
J K Cruickshank1, A H Heald, S Anderson
1Clinical Epidemiology Group, Unit of Chronic Disease Epidemiology, University of Manchester Medical School, Manchester, England. clinep@man.ac.uk
Abstract:
The insulin-like growth factor (IGF) system, comprising insulin-like growth factor I (IGF-I), insulin-like growth factor II (IGF-II), and their binding proteins (IGFBPs), is linked to cell growth, the development of cardiovascular disease, and several cancers. Little is known about its epidemiology. The authors studied relations of the IGF system to anthropometric and metabolic variables in three population-based ethnic groups in Manchester, England, in 1994-1998 with differing disease risks: African Caribbean (n = 193), Pakistani (n = 130), and local Europeans(n = 142). Standardized anthropometry, glucose tolerance tests, and serum assays were performed. Body mass indices (BMIs) were high in all groups. IGF-I levels were highest in normoglycemic African Caribbeans and declined with age (r = -0.28). IGF-II levels were greatest in Europeans. IGFBP-1 concentrations increased with age in Pakistanis (r = 0.20) and Europeans (r = 0.29), but not in African Caribbeans (r = 0.06), and were inversely related to BMI (r = -0.37). Age- and sex-adjusted IGFBP-1 was inversely related to fasting insulin and proinsulin in all groups; participants with newly detected diabetes were relatively insulinopenic but had higher IGFBP-1 concentrations. Nonesterified (free) fatty acid (NEFA) concentrations increased with declining glucose tolerance. In multiple regression analysis, IGFBP-1 was independently and negatively related to fasting insulin, BMI, and African-Caribbean compared with European ethnicity but positively related to age, fasting glucose, and NEFA. IGF-I was inversely related only to age, NEFA, and Pakistani ethnicity. IGF-II showed a strong ethnic difference but was unrelated to other variables. These data indicate considerable potential for exploring disease-IGF system relations in population samples.
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