Author
Beisiegel, Jeannemarie | |
Glahn, Raymond | |
Welch, Ross | |
MENKIR, ABEBE - INTER INST TROP AGRI | |
MAZIYA-DIXON, BUSSIE - INTER INST TROP AGRI | |
Hunt, Janet |
Submitted to: Federation of American Societies for Experimental Biology Conference
Publication Type: Abstract Only Publication Acceptance Date: 11/10/2005 Publication Date: 3/6/2006 Citation: Beisiegel, J.M., Glahn, R.P., Welch, R.M., Menkir, A., Maziya-Dixon, B.B., Hunt, J.R. 2006. A caco-2 cell model predicts relative iron absorption from tropical maize by women [abstract]. FASEB J. 20(4):A624. Interpretive Summary: Technical Abstract: Fe absorption from the tropical maize variety, ACR90POOL16-DT (ACR), previously found to have similar Fe content, but higher Fe bioavailability in vitro, was compared with a control variety, TZB-SR (TZB), in 26 non-anemic women, 21-48 y, with serum ferritin 3-248 µg/L. Porridge made from 50 g dw corn with extrinsic 55Fe or 59Fe was consumed w/wo orange juice (~40 mg ascorbate; AA). Fe absorption, determined from 14-d isotope retention in whole body and blood, did not differ between ACR [2.2% (1.7, 2.7); geom. mean (± 1 SEM)] and TZB [2.0% (1.6, 2.5)]. With the difference in Fe content (840 vs. 710 µg/meal), Fe absorbed from ACR tended to be higher than TZB [18 (15, 23) vs. 14 (11, 18) µg/meal; P = 0.07]. AA greatly increased (P<0.0001) Fe absorbed from ACR [58 µg (46, 73)] and TZB meals [51 µg (41, 64)], again with unsubstantial differences between varieties. Tested with the Caco-2 model, identical meals induced no difference in ferritin formation (ng/mg cell protein) between varieties alone (ACR 33 ± 4 vs. TZB 37 ± 10; mean ± SD) or with AA (ACR 174 ± 34 vs. TZB 165 ± 37). The absorption ratio in humans (2.6 w/wo AA) was effectively predicted by the Caco-2 model (2.7) using the conversion of Yun et al (J Nutr, 2004). Small differences in Fe content or bioavailability between cultivars may not persist across growing seasons. AA-rich foods can substantially enhance Fe absorption and the Caco-2 model is a valid tool for quantitatively predicting this enhancement. Funded by IITA, USAID and USDA-ARS. |