Elsevier

Neurobiology of Aging

Volume 36, Issue 4, April 2015, Pages 1678-1685
Neurobiology of Aging

Regular article
Effects of diet on brain iron levels among healthy individuals: an MRI pilot study

https://doi.org/10.1016/j.neurobiolaging.2015.01.010Get rights and content

Abstract

Increased brain iron levels may be a risk factor for age-related neurologic disorders. Little is known about factors other than age and sex potentially affecting brain iron concentration. We investigated dietary habits (iron and calcium supplements, dairy products, vegetables, and red meat) as a potential modifiable predictor of brain iron levels using 3-T susceptibility-weighted magnetic resonance imaging. One hundred ninety volunteers were scanned, and mean phase and mean phase of low-phase voxels were determined for deep gray-matter (DGM) structures, including the caudate, putamen, thalamus, pulvinar, hippocampus, amygdala, red nucleus, and substantia nigra. There was a trend for lower mean phase (suggestive of high iron levels) in individuals taking iron supplements (p = 0.075). Among men, both increased dairy and vegetable intakes were significantly associated with lower DGM mean phase (p < 0.05) and mean phase of low-phase voxels (p < 0.05) in the thalamus, pulvinar, and red nucleus. In contrast, among women, iron levels were not associated with dairy consumption (p > 0.05) in the DGM but were inversely associated with vegetable intake in the thalamus (p = 0.006). Brain iron levels appear to be modulated by diet, with effects being highly dependent on gender.

Introduction

Brain iron deposition occurs in a multitude of neurologic and neurodegenerative conditions (Haacke et al., 2005, Hagemeier et al., 2012, Ward et al., 2014). In addition, in healthy aging, brain iron levels are known to increase, with concentrations plateauing in mid-adulthood (Batista-Nascimento et al., 2012, Hagemeier et al., 2013, Pfefferbaum et al., 2009, Sadrzadeh and Saffari, 2004, Xu et al., 2008). Different brain structures also accumulate iron at different rates (Pfefferbaum et al., 2009, Xu et al., 2008), and women tend to have lower levels of brain iron and total body iron compared with men (Hagemeier et al., 2013, Sadrzadeh and Saffari, 2004). So far, although pathologic mechanisms behind iron accumulation are actively being investigated (Ward et al., 2014, Williams et al., 2012), little is known about possible environmental factors influencing brain iron concentrations. In fact, whether environmental factors can significantly influence iron concentrations is up for debate. One apparent environmental source of brain iron is through the same mechanism most systemic iron is acquired: dietary intake. Because brain iron levels have been proposed as a biomarker and a risk factor for neurodegenerative disorders (Bartzokis et al., 2007, Xu et al., 2008), investigating the possible role of dietary factors influencing this relationship is important.

Iron is a cofactor in many vital biochemical reactions including oxidative phosphorylation, myelin synthesis, neurotransmitter production, and oxygen transport (Crichton et al., 2011) and is, therefore, an essential element for proper biological functioning. However, it has been postulated that abnormal iron concentrations, as observed in several neurologic conditions, can enhance pathology (Williams et al., 2012), for example, by increasing protein misfolding and aggregation (Ostrerova-Golts et al., 2000). Iron can catalyze the production of reactive oxygen species, which lead to oxidative tissue damage (LeVine and Chakrabarty, 2004) and contribute to cell death (Dixon and Stockwell, 2014). The increased inflammation and activated state of microglia (Dheen et al., 2007) may be particularly damaging in disorders such as multiple sclerosis (Williams et al., 2012).

Blood iron homeostasis is maintained primarily by the recycling of iron by senescent erythrocytes and from dietary sources (Ganz and Nemeth, 2012). Most dietary iron is absorbed in the duodenum of the intestines (Sadrzadeh and Saffari, 2004). Heme iron (mostly sourced from meat) has greater bioavailability than nonheme iron (mostly plant sources) (Hallberg, 1983). Uptake of nonheme iron is thought to be dependent on bodily iron status. Red meat is a major dietary source of heme iron, with >60% of iron in beef being in the form of heme iron (Valenzuela et al., 2009). Uptake of heme iron is mostly independent of bodily iron status, with red meat and fish consistently enhancing the absorption of dietary iron (Hallberg, 1983, Williams, 2007). It has also been suggested that iron absorption depends on meal composition (Hallberg, 1983). For example, vegetarians have been found to have a lower rate of absorption of nonheme iron that can be attributed to phytic acid in many nonmeat dietary staples (e.g., whole grains, nuts, legumes, lentils, eggs, and soy protein), which inhibit nonheme iron absorption (Hunt, 2003). Indeed, women on an ovo-lacto–vegetarian diet showed 70% lower nonheme iron absorption and a concomitant decrease in ferritin (the most prominent iron storage protein) excretion, compared with women on a nonvegetarian diet in an 8-week study (Hunt and Roughead, 1999). However, serum ferritin levels were minimally influenced (Hunt and Roughead, 1999). Other factors found to inhibit iron absorption include phytate (cereals and legumes), polyphenols (teas, chili, cereals, legumes, and casein and whey), and milk products (egg protein, soy proteins, and calcium) (Hallberg, 1983, Hurrell and Egli, 2010, Tuntipopipat et al., 2006). Also, high-fat diets have been found to result in systemic iron deficiency in mice (Sonnweber et al., 2012). Ascorbic acid (vitamin C, from, e.g., peppers, broccoli, berries, citrus fruits, and other fruits and vegetables), meat, and fish enhance iron absorption (Hallberg, 1983, Hurrell and Egli, 2010). For example, the administrations of ascorbic acid can overcome the effects of iron absorption inhibitors (Hurrell and Egli, 2010).

To our knowledge, little research has been carried out on the effects of dietary factors on iron levels in the human central nervous system (CNS). Some work has been carried out in the animal studies, where it has, for example, been found in rats that iron-deficient or iron-rich diets decrease and increase brain iron concentrations, respectively (Pinero et al., 2000). In rhesus monkeys, caloric restriction has been observed to decrease brain iron levels (Kastman et al., 2012). These and other animal studies (Dwork, 1995, Jellen et al., 2013) lend credence to the notion that dietary factors may influence not only systemic iron but also brain iron levels.

Because the relationship of possible dietary factors influencing iron uptake and brain iron levels have not been well studied in humans, we conducted a preliminary investigation on individuals who both filled out a self-report questionnaire regarding basic dietary factors and who received magnetic resonance imaging (MRI) with susceptibility-weighted imaging (SWI). The paramagnetism of tissue iron causes a negative shift of the SWI phase in iron-laden regions relative to surrounding brain parenchyma (Hagemeier et al., 2013, Pfefferbaum et al., 2009, Wang et al., 2012, Xu et al., 2008) and, hence, allows to assess tissue iron in vivo. The filtered phase measures employed in the present work provide an indirect estimate of the iron content of the deep gray-matter (DGM) structures, the so-called putative iron concentration.

Section snippets

Participants

This study used data from an ongoing prospective study of genetic and environmental risk factors in multiple sclerosis that enrolled >1000 individuals with multiple sclerosis, healthy individuals, and other neurologic diseases (Foster et al., 2012, Gabelic et al., 2014). One hundred and ninety healthy volunteers without any known CNS pathology were recruited for this substudy of diet and brain iron. Mean age of participants was 43.2 (standard deviation = 16) years. There were 129 women and 61

Gender differences

Women were more likely to take iron (p = 0.012) and calcium supplements (p < 0.001). The proportion of those who consumed dairy was similar between men and women, but men had a higher rate of consumption (p = 0.017, Table 1). Men consumed more red meat than women (p < 0.001) and did so more frequently (p < 0.001, Table 1).

Dietary consumption and SWI measures

ANCOVA adjusting for age and sex was performed to investigate SWI differences between individuals that took iron or calcium supplements, were vegetarians, or consumed dairy,

Discussion

The potential effects of diet on brain iron levels have not been well defined in humans and only minimally among other primates (Kastman et al., 2012). To our knowledge, this is the first study investigating potential dietary influences on in vivo measured brain iron levels in a population of healthy individuals. Increased iron concentrations can have detrimental effects by causing tissue destruction through the generation of reactive oxygen species (Dixon and Stockwell, 2014, Zecca et al., 2004

Conclusions

The present pilot study shows that dietary intake of certain foods is associated with putative DGM brain iron levels as measured by SWI. Iron supplement intake itself, however, was only weakly associated with brain iron levels in this sample. In men, higher dairy consumption was associated with lower mean phase and MP-LPV, both indicative of increased iron levels, in the subcortical DGM, most prominently the thalamus and its pulvinar nucleus. Overall, prominent gender differences were observed;

Disclosure statement

Conflict of interest: Dr Hagemeier, Dr Tong, and Dr Schweser have nothing to disclose. Dr Ramanathan received research funding or consulting fees from EMD Serono, Biogen Idec, Pfizer, the National Multiple Sclerosis Society, the Department of Defense, Jog for the Jake Foundation, the National Institutes of Health, and National Science Foundation. He received compensation for serving as an Editor from the American Association of Pharmaceutical Scientists. These are unrelated to the research

Acknowledgements

Drs JH, OT, MGD, FS, MR, and RZ substantially contributed to the concept and design of the study. Drs JH and RZ drafted the article, whereas all the authors revised it critically for important intellectual content. Dr JH performed the statistical analysis. All the authors had access to the data.

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