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. 2002 Feb 19;99(4):2264-9.
doi: 10.1073/pnas.261708798.

Iron deficiency and iron excess damage mitochondria and mitochondrial DNA in rats

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Iron deficiency and iron excess damage mitochondria and mitochondrial DNA in rats

Patrick B Walter et al. Proc Natl Acad Sci U S A. .

Abstract

Approximately two billion people, mainly women and children, are iron deficient. Two studies examined the effects of iron deficiency and supplementation on rats. In study 1, mitochondrial functional parameters and mitochondrial DNA (mtDNA) damage were assayed in iron-deficient (< or =5 microg/day) and iron-normal (800 microg/day) rats and in both groups after daily high-iron supplementation (8,000 microg/day) for 34 days. This dose is equivalent to the daily dose commonly given to iron-deficient humans. Iron-deficient rats had lower liver mitochondrial respiratory control ratios and increased levels of oxidants in polymorphonuclear-leukocytes, as assayed by dichlorofluorescein (P < 0.05). Rhodamine 123 fluorescence of polymorphonuclear-leukocytes also increased (P < 0.05). Lowered respiratory control ratios were found in daily high-iron-supplemented rats regardless of the previous iron status (P < 0.05). mtDNA damage was observed in both iron-deficient rats and rats receiving daily high-iron supplementation, compared with iron-normal rats (P < 0.05). Study 2 compared iron-deficient rats given high doses of iron (8,000 microg) either daily or every third day and found that rats given iron supplements every third day had less mtDNA damage on the second and third day after the last dose compared to daily high iron doses. Both inadequate and excessive iron (10 x nutritional need) cause significant mitochondrial malfunction. Although excess iron has been known to cause oxidative damage, the observation of oxidant-induced damage to mitochondria from iron deficiency has been unrecognized previously. Untreated iron deficiency, as well as excessive-iron supplementation, are deleterious and emphasize the importance of maintaining optimal iron intake.

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Figures

Figure 1
Figure 1
Relationship between mitochondrial 1/RCR and mtDNA fragmentation and liver nonheme-iron levels. (A) Representative Southern blots from the four groups showing mtDNA forms and fragments. mtDNA fragmentation was determined by using densitometry of digitized images from Southern blots of agarose gels, as described in Materials and Methods. (B) Nonlinear correlation between 1/ln-RCR (left ordinate), ln-mtDNA fragmentation normalized to supercoiled mtDNA (right ordinate) and ln-nonheme liver-iron stores. Boxes (□) represent averages from 12 animals ± SE; regression analysis was performed using all data points (n = 48). Mitochondria and mtDNA were isolated from iron-deficient rats (○), iron-normal control rats (⋄), daily high-iron-supplemented iron-normal rats (♦), and daily high-iron-supplemented iron-deficient rats (●), as described in Materials and Methods. RCR was determined by measuring the ratio of state 3 to state 4 oxygen consumption by using a Clark-type oxygen electrode, as described in Materials and Methods.
Figure 2
Figure 2
Relationship between liver nonheme iron and DCF fluorescence (A) and Rh123 fluorescence (B and C) in PMNs and lymphocytes in rats. PMNs and lymphocytes were isolated from the different iron treatment groups (as in Fig. 1) as described in Materials and Methods. Boxes (□) represent averages of ln-DCF (right ordinate) or ln-Rh123 fluorescence (left ordinate, mean channel number) from six animals ± SE from each iron-treatment group. Cells were collected immediately after the blood draw and subjected to flow cytometry, as described in Materials and Methods. Nonlinear regression analysis was performed using all data points (24 animals).
Figure 3
Figure 3
Analysis of nonlinear regression models: comparison of an overall model and individual models of Z-transformed values of the six dependent variables vs. liver ln-nonheme iron. Each of the six dependent variables (five were analyzed by nonlinear regression, as shown in Figs. 1 and 2) was transformed to a Z score and modeled as a quadratic function, using ln-liver nonheme iron as the independent variable. The equation for the RCR ratio's Z score was obtained from inverted RCR values (1/RCR, a measure of inefficiency), resulting in normal rats having lower rather than higher values. Each model line was obtained from nine values of liver iron. All statistics were performed as described in Materials and Methods.

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