Aging, gender, and the elderly adult brain: An examination of analytical strategies
Introduction
Numerous studies have documented the ways in which the healthy adult brain changes with age. In general, brain parenchyma atrophies as a result of aging, while cerebrospinal fluid (CSF) and white-matter lesions correspondingly increase in volume [1], [2], [3], [7], [8], [15], [18], [21], [22], [23], [28], [29], [35], [41], [43], [46], [49], [51], [55], [56], [57]. This decrease in parenchymal volume has generally been attributed to atrophy of gray matter [5], [8], [21], [28], [35], [41], [43], [45], [48], [23], particularly cortical thinning [50], and may result from cell-body atrophy or the outright death of cells [44]. Gray-matter atrophy is in turn thought to enable the increase in CSF volume [28], [35], [41], [43]. The effects of aging on white matter are not as clear, however. Many studies have found a decrease in white-matter volume [2], [16], [23], [29], [33], [34], [45], [48], [49], [57], perhaps because of demyelination [44]. Several of these studies have reported nonlinear rates of decline, particularly in the elderly, with studies reporting significant quadratic [16], [57] or cubic [2] rates of decline. Other studies, however, report no age-related change in total white-matter volume [18], [28], [35], [41], [43], [55], and some even report an increase [8], [21].
Aging also affects specific cortical and subcortical brain structures. The basal ganglia shrink with age [55], [59], [33]. Structures within the basal ganglia also show age-related atrophy, including the caudate [14], [20], [24], [25], [28], [31], [32], [38], [39], [40], [47], [52], [57], the lentiform nucleus (comprised of the putamen and the globus pallidus) [28], [39], and the putamen itself [24], [25], [37], [40], [47], [52], [57]. One study reported a small age-related decrease in the basal ganglia involving only the head of the caudate and the putamen; the body of the caudate showed no decline [21]. Many studies of the hippocampus have found that it shrinks with age as well [2], [10], [13], [29], [33], [38], [46], [48], [57], [18], [34], [54].
Other investigations have examined gender differences in brain volumes; in particular, they have tried to determine if age-related changes are gender-dimorphic. Previous reports of gender differences have generally indicated smaller gray-matter structures in males after controlling for whole-brain volume or body size. Some studies have reported age–sex interactions, with atrophy of the male brain beginning at an earlier age and progressing more rapidly [11], [22], [38], [46], [47], [52], [59]. More recent studies, however, tend to find no interactions [2], [16], [18], [33], [34], [49], [50], [58].
There have been numerous reports of hemispheric differences in the brain, some of which report aging and gender differences that are more substantial on one side of the brain than the other. In many studies, the right hemisphere is found to be larger than the left [22], [45], [59], [46]. For specific brain regions, this relation may not be as consistent, with some structures larger in the left hemisphere and others larger in the right [45], [46], [48], [54], [56], [58]. Studies of the basal ganglia have been particularly contradictory; two studies report a larger right caudate [27], [47] and two report a larger left caudate [20], [25]. One longitudinal study has reported that gray-matter atrophy is more substantial in the right hemisphere [49]. Two studies have suggested that patterns of hemispheric atrophy differ between genders, finding that hemispheric atrophy was symmetric in women, but more severe in the left hemisphere in men [11], [22], [59]. Females have smaller hippocampi than males, even after adjusting for body size [45]; moreover, the female hippocampus is thought to shrink more rapidly [21], [38], though there have been some contradictory studies [17], [46].
Most of the studies cited above had a small number of subjects; of those that had a sample size over 140, almost all included subjects ranging in age from 15 to 93, with only a smaller number of elderly. Moreover, many of these studies did not provide quantitative estimates of the rate of atrophy, instead presenting correlations or analyses of variance that compared different age groups; others have used relatively imprecise rating scales, particularly when measuring white-matter hyperintensities. Given previous findings of an increase in the rate of decline among the elderly [1], we decided to focus on an elderly population. We investigated the rate of volume change in gray and white-matter tissue, cerebrospinal fluid, and lesions, as well as the caudate, putamen, and hippocampus. We sought to address several issues (for a similar approach, see [4]): Can we provide precise, quantitative estimates of brain atrophy, laterality, and gender differences? In particular, what is the relation between white-matter decline and aging in an older population? To what extent do these estimates change depending on the kind of analyses and covariates that are used?
Based on previous results, we predicted that gray-matter volumes, including those of smaller gray-matter structures, would be negatively correlated with age while CSF volumes would be positively correlated. Furthermore, given that we were focusing on an elderly population, we predicted that white-matter volumes would be negatively correlated with age as well. We also predicted that the choice of covariate would not substantially change the results of these analyses [4]. For the gender analyses, we predicted that the use of the covariates would make a difference: uncorrected volumes were expected to be larger in men than in women; corrected volumes were expected to be larger in women than in men, with the exception of the hippocampus.
Section snippets
Study population
The study population was recruited from a pool of normal elderly used as controls for studies on depression. MRI data on these controls have been used in several previous studies [42], [53]. Eligible controls had a non-focal neurological examination, no self-report of neurologic or depressive illness, and no evidence of depression. Eligibility for this study was restricted to those aged 60 years or older who could speak and write English. Exclusion criteria included (1) another major
Demographics and group differences
Table 1 presents the demographics of our sample and the number of scans that were available for each brain structure. Independent-samples t-tests (two-tailed) showed that there were no significant differences in education or age between males and females, and effect sizes as measured by ω2 were minimal. (For age, t(1,138) = −0.69, p < 0.49, ω2 = 0.003; for education, t(1,138) = 1.44, p < 0.15, ω2 = 0.01.)
Analysis 1: laterality
We tested for hemispheric differences in brain volumes using a mixed-models approach. Structure volume
Discussion
The aging brain changes in many ways, some of which are thought to be lateralized or gender-dimorphic. To date, however, the results of previous studies have often been inconsistent. We sought to address these discrepancies by providing precise estimates of atrophy and applying multiple models to the data.
Overall, we replicated the common finding that, within an elderly population, brain parenchyma decreases with increasing age while CSF and lesion volumes increase. However, examination of
Conclusions
There has been substantial debate over the most useful way to measure differences in brain volumes. Many researchers choose to correct for variation in head size by controlling for the intracranial volume (ICV) or another similar measure. Some researchers use this measure to calculate structure ratios, which are then used as the dependent variable [e.g. 1]; others use it as a covariate in an analysis of covariance or multiple regression analysis [22]. Raz et al. [45] argued that the use of head
Acknowledgements
The authors would like to thank Tim Blitchington for the development of the GRID Program, Dr. Chris Byrum for assistance in developing neuroanatomical guidelines, and Dr. Carl Pieper for statistical advice.
Disclosure statement: The authors hereby declare that they have no current, past, or anticipated conflicts of interest, whether real or potential. All research with human participants was reviewed and approved by the Duke University Institutional Review Board, and informed consent was
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