OBJECTIVES: Several markers of iron metabolism have been associated with insulin resistance (IR) and type 2 diabetes mellitus in cross-sectional studies. However, prospective data on these associations are scarce, and it is currently unclear in which tissues iron metabolism may contribute to IR. Therefore, we investigated whether markers of iron metabolism were associated with IR in muscle, liver, and adipocytes, and with glucose intolerance over a 7-year follow-up period. DESIGN AND METHODS: Serum ferritin, transferrin, total iron, non-transferrin-bound iron, and transferrin saturation were determined at baseline of a prospective cohort study in 509 individuals (60 % men, age 59 ± 6.9 years, body mass index 28.5 ± 4.3). Both at baseline and after a 7-year follow-up (n = 386), measures of glucose, insulin (during glucose tolerance tests), and non-esterified fatty acids were obtained. Using generalized estimating equations, we investigated associations between baseline iron markers and indices of muscle, liver, and adipocyte insulin resistance (adipocyte IR), as well as glucose intolerance, over the 7-year period. RESULTS: Over a 7-year period, baseline serum ferritin (per 10 μg/L increase) was positively associated with homeostasis model assessment insulin resistance (HOMA2-IR) [β = 0.77 % (95 % CI 0.50-1.03)], hepatic insulin resistance (hepatic IR) [β = 0.39 % (0.23-0.55)], adipocyte IR [β = 1.00 % (0.65-1.35)], and AUCglucose [β = 0.32 % (0.18-0.46)] after adjustment for several covariates, including inflammatory markers (all p < 0.001). Similarly, serum transferrin (per 0.1 g/L) was associated with HOMA2-IR [β = 2.66 % (1.55-3.78)], hepatic IR [β = 1.16 % (0.47-1.85)], adipocyte IR [β = 3.75 % (2.27-5.25)], and AUCglucose [β = 1.35 % (0.74-1.96)] over 7 years. CONCLUSIONS: Iron metabolism and related factors may contribute to IR in muscle, liver, and adipocytes, eventually leading to impaired glucose metabolism and hyperglycaemia.
OBJECTIVES: Several markers of iron metabolism have been associated with insulin resistance (IR) and type 2 diabetes mellitus in cross-sectional studies. However, prospective data on these associations are scarce, and it is currently unclear in which tissues iron metabolism may contribute to IR. Therefore, we investigated whether markers of iron metabolism were associated with IR in muscle, liver, and adipocytes, and with glucose intolerance over a 7-year follow-up period. DESIGN AND METHODS: Serum ferritin, transferrin, total iron, non-transferrin-bound iron, and transferrin saturation were determined at baseline of a prospective cohort study in 509 individuals (60 % men, age 59 ± 6.9 years, body mass index 28.5 ± 4.3). Both at baseline and after a 7-year follow-up (n = 386), measures of glucose, insulin (during glucose tolerance tests), and non-esterified fatty acids were obtained. Using generalized estimating equations, we investigated associations between baseline iron markers and indices of muscle, liver, and adipocyte insulin resistance (adipocyte IR), as well as glucose intolerance, over the 7-year period. RESULTS: Over a 7-year period, baseline serum ferritin (per 10 μg/L increase) was positively associated with homeostasis model assessment insulin resistance (HOMA2-IR) [β = 0.77 % (95 % CI 0.50-1.03)], hepatic insulin resistance (hepatic IR) [β = 0.39 % (0.23-0.55)], adipocyte IR [β = 1.00 % (0.65-1.35)], and AUCglucose [β = 0.32 % (0.18-0.46)] after adjustment for several covariates, including inflammatory markers (all p < 0.001). Similarly, serum transferrin (per 0.1 g/L) was associated with HOMA2-IR [β = 2.66 % (1.55-3.78)], hepatic IR [β = 1.16 % (0.47-1.85)], adipocyte IR [β = 3.75 % (2.27-5.25)], and AUCglucose [β = 1.35 % (0.74-1.96)] over 7 years. CONCLUSIONS:Iron metabolism and related factors may contribute to IR in muscle, liver, and adipocytes, eventually leading to impaired glucose metabolism and hyperglycaemia.
Authors: Benjamin J Ryan; Douglas W Van Pelt; Lisa M Guth; Alison C Ludzki; Rachel A Gioscia-Ryan; Chiwoon Ahn; Katherine L Foug; Jeffrey F Horowitz Journal: Exp Physiol Date: 2018-10-08 Impact factor: 2.969
Authors: Clara Podmore; Karina Meidtner; Matthias B Schulze; Robert A Scott; Anna Ramond; Adam S Butterworth; Emanuele Di Angelantonio; John Danesh; Larraitz Arriola; Aurelio Barricarte; Heiner Boeing; Françoise Clavel-Chapelon; Amanda J Cross; Christina C Dahm; Guy Fagherazzi; Paul W Franks; Diana Gavrila; Sara Grioni; Marc J Gunter; Gaelle Gusto; Paula Jakszyn; Verena Katzke; Timothy J Key; Tilman Kühn; Amalia Mattiello; Peter M Nilsson; Anja Olsen; Kim Overvad; Domenico Palli; J Ramón Quirós; Olov Rolandsson; Carlotta Sacerdote; Emilio Sánchez-Cantalejo; Nadia Slimani; Ivonne Sluijs; Annemieke M W Spijkerman; Anne Tjonneland; Rosario Tumino; Daphne L van der A; Yvonne T van der Schouw; Edith J M Feskens; Nita G Forouhi; Stephen J Sharp; Elio Riboli; Claudia Langenberg; Nicholas J Wareham Journal: Diabetes Care Date: 2016-02-09 Impact factor: 19.112
Authors: Wijtske Annema; Arne Dikkers; Jan Freark de Boer; Marleen M J van Greevenbroek; Carla J H van der Kallen; Casper G Schalkwijk; Coen D A Stehouwer; Robin P F Dullaart; Uwe J F Tietge Journal: Sci Rep Date: 2016-06-08 Impact factor: 4.379
Authors: Min Kyoung Kim; Seung Joo Chon; Yeon Soo Jung; Bo Ok Kim; Eun Bee Noe; Bo Hyon Yun; SiHyun Cho; Young Sik Choi; Byung Seok Lee; Seok Kyo Seo Journal: PLoS One Date: 2016-06-23 Impact factor: 3.240