Elsevier

NeuroImage

Volume 54, Issue 2, 15 January 2011, Pages 750-759
NeuroImage

Differential effects of age and history of hypertension on regional brain volumes and iron

https://doi.org/10.1016/j.neuroimage.2010.09.068Get rights and content

Abstract

Aging affects various structural and metabolic properties of the brain. However, associations among various aspects of brain aging are unclear. Moreover, those properties and associations among them may be modified by age-associated increase in vascular risk. In this study, we measured volume of brain regions that vary in their vulnerability to aging and estimated local iron content via T2* relaxometry. In 113 healthy adults (19–83 years old), we examined prefrontal cortex (PFC), primary visual cortex (VC), hippocampus (HC), entorhinal cortex (EC), caudate nucleus (Cd), and putamen (Pt). In some regions (PFC, VC, Cd, and Pt) age-related differences in iron and volume followed similar patterns. However, in the medial–temporal structures, volume and iron content exhibited different age trajectories. Whereas age-related volume reduction was mild in HC and absent in EC, iron content evidenced significant age-related declines. In hypertensive participants significantly greater iron content was noted in all examined regions. Thus, iron content as measured by T2* may be a sensitive index of regional brain aging and may reveal declines that are more prominent than gross anatomical shrinkage.

Research Highlights

►Aging differentially affects regional brain volume and iron concentration, but the relative magnitude of those effects have not been compared in vivo. ►In a sample of healthy adults, we observed similar patterns of age-related differences in volume and T2* (index of iron) neocortex and neostriatum content. ►In contrast, in the medial–temporal structures, iron accumulation showed stronger association with age than volume did. ►Hypertensive participants exhibited higher iron concentration than normotensives of the same age. ►Iron content as measured by T2* may be a sensitive index of regional brain aging.

Introduction

Aging, even in healthy individuals, is associated with significant brain changes. One of the best established changes in the aging brain is differential brain shrinkage that is prominent in the polymodal association cortices, striatum, and cerebellum and minimal in the primary sensory cortices (Fjell et al., 2009, Pfefferbaum et al., 1998, Raz et al., 2005; for a review see Raz and Rodrigue, 2006, Resnick et al., 2003). However, age effects on the brain are not limited to gross neuroanatomy but appear at multiple levels of analyses, including neurochemistry, vascular function, and neural connectivity (Bäckman et al., 2006, Hedden and Gabrieli, 2004, Madden et al., 2009; see Raz and Kennedy, 2009 for reviews). Furthermore, all aspects of brain aging are sensitive to numerous physiological, environmental, and genetic factors. The relationship among structural and metabolic aspects of brain aging and the role of physiological and neurochemical modifiers remain unclear.

One of the most prominent metabolic differences associated with brain aging is alteration of iron homeostasis (Andrews and Schmidt, 2007). Although indispensable in diverse physiological and neurochemical processes, iron is a potent agent of oxidative stress and neurodegeneration (Zecca et al., 2004). In the brain, iron is present in several forms. Ferric heme iron in the hemoglobin molecule makes deoxyhemoglobin paramagnetic (Pauling and Coryell, 1936) and creates local inhomogeneity detectable through magnetic resonance imaging (MRI) via change in T2* relaxation times (Ogawa et al., 1990). Thus, differences in T2* can indicate heme iron content. In addition to heme iron in blood that dynamically alters T2*, the brain contains non-heme iron predominantly sequestered in ferritin (Schenck and Zimmerman, 2004). Brain distribution of non-heme iron is uneven and its highest concentration is in the motor nuclei (Hallgren and Sourander, 1958, Haacke et al., 2005). Regional non-heme iron content increases with age (Hallgren and Sourander, 1958, Schenck and Zimmerman, 2004), and in the aging brain there is another contributor of non-heme iron that can alter T2*: iron-rich amyloid plaques (Collingwood et al., 2008, Quintana et al., 2006).

In a comparison of adults with Alzheimer's disease (AD) and mild cognitive impairment to normal controls, Rombouts et al. (2007) found significant reduction of T2* in the hippocampus, posterior cingulate gyrus and precuneus, parietal lobe, insula and putamen of AD patients. However, due to image filtering and smoothing, the validity of regional interpretation in this study is unclear. Recently, Sullivan et al. (2009) used field dependent relaxation rate measures of T2* in a small sample of older adults, and observed significant associations between the T2* values in the basal ganglia and thalamus and cognitive and motor task performance. Notably, the regions examined in that study included neither neocortex nor hippocampus.

Few studies applied T2* relaxometry to investigation of the aging brain (Haacke et al., 2005). In early attempts, age-related reduction in T2* signal was observed in the entorhinal cortex (EC) of older adults (Small et al., 1999, Small et al., 2002), and interpreted as reduction of resting metabolism. However, in those studies, signal intensity, not true T2* values, was measured from a single slice. Other studies found age-related declines in T2* in superior frontal gyrus, hippocampus and entorhinal cortex (Raz et al., 2007a), striatum (Siemonsen et al., 2008, Cherubini et al., 2009, Haacke et al., 2010), globus pallidus (Aquino et al., 2009, Pfefferbaum et al., 2009), and the thalamus (Haacke et al., 2010). Although T2* may not be the ideal in vivo index of brain iron (Haacke et al., 2005), it is nonetheless a sufficiently robust correlate of iron content (Ordidge et al., 1994, Martin et al., 1998, Martin et al., 2008, Péran et al., 2009, Duyn et al., 2007, Yao et al., 2009, Shmueli et al., 2009). Although R2* (= 1/T2*) is the sum of spin–spin relaxation rates, R2 (= 1/T2), and the inhomogeneity-induced relaxation rate R2′ (= 1/T2′), in regions with very little myelin the reciprocal of R2* but not R2, correlate highly with iron concentration across a wide range of field strengths (Péran et al., 2009, Yao et al., 2009). From these data, one can conclude that shortening of T2* is a good proxy for increased iron content. Despite this good correlation, others have suggested that the addition of phase information improves estimates of iron concentration in the basal ganglia (Pfefferbaum et al., 2009). Moreover, the correlations between age and T2* in the basal ganglia are driven almost entirely by iron-sensitive T2′ and not by T2 (Siemonsen et al., 2008).

An important factor not addressed in the reviewed studies of T2* in the aging brain, is the influence of vascular risk. Hypertension, one of the most common vascular risk factors, negatively affects brain structure (Burgmans et al., 2010, DeCarli et al., 1995, Gianaros et al., 2006, Raz et al., 2003, Salerno et al., 1992). It is also linked to cerebral microbleeds (CMB), which contain paramagnetic hemosiderin (Harrison and Arosio, 1996, Viswanathan and Chabriat, 2006). Thus, hypertension may have an additional impact on T2* beyond the effects of aging.

In summary, prior studies suggest that through T2* relaxometry, regional differences in heme and non-heme iron content can be detected in normal aging and age-related cognitive disorders. However, regional distribution of T2* values, their relation to age and to structural properties affected by aging, and the role of vascular risk in those associations remain unclear. The goals of the present study were threefold. First, we investigated age differences in iron content indexed by T2* values across several brain regions that differ in their sensitivity to aging. Second, we compared the pattern of age differences in local T2* values to the pattern of volume shrinkage in the corresponding regions and evaluated the relationship between two types of indices of brain aging. Third, we sought to determine whether a vascular risk factor such as hypertension could affect the strength of association between age and regional indices of iron content.

Section snippets

Participants

The sample consisted of 113 participants recruited through media advertisements and paid for their participation. About 61% of the participants were from a previous preliminary study (Raz et al., 2007a). Persons with a history of cardiovascular, neurological or psychiatric disease, use of anti-seizure medication, anxiolytics, or antidepressants, head trauma with loss of consciousness for more than 5 min, thyroid problems, diabetes mellitus, drug and alcohol problems were excluded from the study.

Age-related regional differences in T2*

The analysis revealed a significant main effect of age on T2*: F(1, 110) = 93.50, p < .001. Advanced age was associated with shorter T2* across the sampled ROIs, with the correlation between age and mean T2* r = .68, p < .001. No effect of sex or its interaction with other variables was found. The within-subjects main effect of ROI was significant and reflected significant regional differences in T2* values: F(5, 550) = 122.55, p < .001. See Table 2 for regional means.

Notably, a significant Age × ROI

Discussion

To the best of our knowledge, this is the first study to examine in vivo the relationship between regional brain iron content and age-related differences in regional brain volumes in healthy adults. An excellent correspondence between the T2* values and regional concentrations of non-heme iron (from Table 3, Haacke et al., 2005), supports the validity of T2* as an index of iron content (see Fig. 6). Although we observed age-related increase in iron content, the regional pattern of T2*

Conclusions

In conclusion, the results of this study show that regional iron concentration is a sensitive index of brain aging. In longitudinal study, in vivo assessment of regional content of brain iron may shed light on the origins of age-related regional brain shrinkage. Moreover, altered iron metabolism may mediate exacerbation of brain aging by vascular risk factors. The mechanisms underpinning the relative contribution of various types of iron to age-related T2* shortening remain to be determined.

Acknowledgments

The work was supported by the National Institutes of Health (grants R37 AG-011230 to NR, training grant T32 HS-013819 to KR via the Institute of Gerontology), and a Dissertation Award from the American Psychological Association (to KR). We thank Hanzhang Lu for valuable comments.

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