Iron Metabolism and Type 2 Diabetes Incidence

OBJECTIVE: Observational studies show an association between ferritin and type 2 diabetes (T2D), suggesting a role of high iron stores in T2D development. However, ferritin is influenced by factors other than iron stores, which is less the case for other biomarkers of iron metabolism. We investigated associations of ferritin, transferrin saturation (TSAT), serum iron, and transferrin with T2D incidence to clarify the role of iron in the pathogenesis of T2D. RESEARCH DESIGN AND METHODS: The European Prospective Investigation into Cancer and Nutrition-InterAct study includes 12,403 incident T2D cases and a representative subcohort of 16,154 individuals from a European cohort with 3.99 million person-years of follow-up. We studied the prospective association of ferritin, TSAT, serum iron, and transferrin with incident T2D in 11,052 cases and a random subcohort of 15,182 individuals and assessed whether these associations differed by subgroups of the population. RESULTS: Higher levels of ferritin and transferrin were associated with a higher risk of T2D (hazard ratio [HR] [95% CI] in men and women, respectively: 1.07 [1.01-1.12] and 1.12 [1.05-1.19] per 100 μg/L higher ferritin level; 1.11 [1.00-1.24] and 1.22 [1.12-1.33] per 0.5 g/L higher transferrin level) after adjustment for age, center, BMI, physical activity, smoking status, education, hs-CRP, alanine aminotransferase, and γ-glutamyl transferase. Elevated TSAT (≥45% vs. <45%) was associated with a lower risk of T2D in women (0.68 [0.54-0.86]) but was not statistically significantly associated in men (0.90 [0.75-1.08]). Serum iron was not associated with T2D. The association of ferritin with T2D was stronger among leaner individuals (Pinteraction < 0.01). CONCLUSIONS: The pattern of association of TSAT and transferrin with T2D suggests that the underlying relationship between iron stores and T2D is more complex than the simple link suggested by the association of ferritin with T2D.We thank all EPIC participants and staff for their contribution to the study. We thank Nicola Kerrison (MRC Epidemiology Unit, Cambridge) for managing the data for the InterAct Project. We thank Dr Felix Day (MRC Epidemiology Unit, Cambridge) for assistance with figures. Funding for the InterAct project was provided by the EU FP6 programme (grant number LSHM_CT_2006_037197). In addition, InterAct investigators acknowledge funding from the following agencies: IS, JWJB and YTvdS: Verification of diabetes cases was additionally funded by NL Agency grant IGE05012 and an Incentive Grant from the Board of the UMC Utrecht (The Netherlands); HBBdM, AMWS and DLvdA: Dutch Ministry of Public Health, Welfare and Sports (VWS), Netherlands Cancer Registry (NKR), LK Research Funds, Dutch Prevention Funds, Dutch ZON (Zorg Onderzoek Nederland), World Cancer Research Fund (WCRF), Statistics Netherlands (The Netherlands); FLC: Cancer Research UK; PWF: Swedish Research Council, Novo nordisk, Swedish Heart Lung Foundation, Swedish Diabetes Association; JH, KO and AT: Danish Cancer Society; RK: Deutsche Krebshilfe; SP: Associazione Italiana per la Ricerca sul Cancro; JRQ: Asturias Regional Government; MT: Health Research Fund (FIS) of the Spanish Ministry of Health; the CIBER en Epidemiología y Salud Pública (CIBERESP), Spain; Murcia Regional Government (Nº 6236); RT: AIRE-ONLUS Ragusa, AVIS-Ragusa, Sicilian Regional Government. Biomarker measurements in the EPIC-InterAct subcohort were partially funded by a grant from the UK Medical Research Council and British Heart Foundation (EPIC-Heart: G0800270). Clara Podmore is funded by the Wellcome Trust (097451/Z/11/Z).This is the author accepted manuscript. The final version is available at http://care.diabetesjournals.org/content/early/2016/01/29/dc15-0257.abstract