Background
MR imaging and segmentation of brain volumes have been increasingly applied in studies of the human brain and its functions. Several studies on aging and age-related cognitive decline have combined neuropsychological tests with MRI findings. These studies have revealed a relationship between regional volumetric atrophy as measured with 3D MRI, decline in memory functions as measured with neuropsychological tests, and the presence of early signs of dementia [
1‐
3].
Although environmental factors contribute to the variation in cognitive function during aging, recent studies have identified genetic markers as significant factors, not only for cognitive function, but also for volumetric variability in aging [
4,
5]. Studies on the genetic basis of cognitive decline and Alzheimer's Disease (AD) have pointed out Apolipoprotein E (APOE), a protein intimately involved in synaptogenesis but also numerous neuropathological processes [
6], as an important marker. The risk of developing AD increases significantly by carrying one or more of the ϵ4-allele of APOE [
7]. ApoEϵ4 is also associated with reduced memory function in patients with mild cognitive impairment (MCI) [
8,
9]. Smith and collaborators [
10] studied a group of MCI patients diagnosed on the basis of memory deficits and found that ApoEϵ4 was associated with poorer performance on tests of learning and recall in MCI patients, but not in normal controls. They suggested that ApoE-related memory deficits are specific cognitive phenotypes in patients with AD pathology. In a group of non-demented older adults, Bondi and collaborators [
11,
12] found memory impairment at study entry in ApoEϵ4 carriers, affecting measures of recall, recognition discriminability, and learning as measured by the California Verbal Learning Test (CVLT).
Combining genetics with volumetric imaging has indicated that regional hippocampal volumes correlate negatively with the zygosity of ApoEϵ4 [
13‐
16]. There are however conflicting results on this topic. Where some studies report no association between hippocampal volumes and APOE genotype [
17‐
19], others have reported mainly longitudinal effects of ApoEϵ4 on hippocampal volumes [
20‐
22], indicating that follow-up studies are more sensitive to pick up associations between APOE genotype and hippocampal volume, than are cross-sectional studies on healthy volunteers.
Furthermore, Tupler et al. [
23] combined MRI-volumes of the hippocampus and APOE genotype in a five year follow-up study to investigate their relative contributions to cognitive decline, as measured by CVLT. The study concluded that, second to previous cognitive testing, ApoEϵ4 predicts memory decline in healthy controls and that MRI-morphometry of the hippocampus added only slightly to the predictive value. However, despite their important prospective design, some methodological weaknesses could be identified in this study. Firstly, the image segmentation and volumetric analysis were performed using manual ROI tracings and several technicians. This adds subjectivity as an error-source in the volumetric analysis. Secondly, the hippocampal volumes were adjusted for cerebral volume, age, sex, and the APOE age interaction. The former might cause a problem, as the cerebrum as a whole continually decreases in size during age [
24,
25], which makes it particularly inappropriate as a normalizing factor. Also, men and women have different volumetric fractions related to cerebrum size [
26]. Another study conducted by Marquis et al. [
27], concluded that previous cognitive test performance and hippocampal volume each predicted onset of questionable dementia, independent of age and sex, whereas possession of the ApoEϵ4 allele did not alter the prediction significantly.
In the present study of 170 normal elderly subjects, we set out to assess the relationship between (i) volumetry of brain structures involved in memory, (ii) genotype of the polymorphic ApoE gene and (iii) scores on the long delay free recall subtest from CVLT (CVLT-LD). Few studies other than Tupler et al. [
23], Lind et al. [
13], and Adak et al. [
28] have combined all three measures to assess the combined predictive value of hippocampal volumes and APOE genotype on episodic memory measures in healthy subjects. Moreover, we have applied a recent multivariate statistical method of conditional inference to investigate the sequential importance of these two variables in predicting CVLT-LD. Our analysis also took into account the effect of age and gender in the analysis, investigating whether these variables could add to the abovementioned predictions.
Although we have performed only a cross-sectional study, in contrast to the repeated and predictive design by Tupler et al. [
23], a major contribution besides conditional inference tree analysis, is the use of semi-automated image processing methods. This is designed to reduce subjectiveness in the analysis. Moreover, we use the total intracranial volume (ICV) as a normalizing factor, a measure which does not change with age. A major point of interest was also whether results from our two geographic groups; the Bergen sample and the Oslo sample, were similar and thereby justify pooling of the samples. We were using the same neuropsychological test procedures and independent use of the same brain segmentation-and volumetric software package, but with different MRI-scanners. This "two-center design" would reinforce the significance of any consistent findings and provide a strong background for further analysis using the methods described.
Discussion
The present study is one of few studies of normal aging where image-derived hippocampal volumes, APOE genotype, and verbal memory performance have been jointly investigated. In our investigation we also included other variables (e.g. age, gender, hippocampus laterality index) that could be important a priori for prediction of verbal memory performance (i.e. CVLT-LD score). Applying the conditional inference model to our multivariate sample, we expected to reveal the sequential importance for each variable in predicting CVLT-LD.
Investigating our results (Figure
6a) we see that gender is the one variable that best predicts CVLT-LD in our sample. This is in concordance with findings in other studies of verbal memory function among elderly normals [
52,
53], where women in general, outperform men [
1,
52]. For men, there were no other variables that could be used to reject the null-hypothesis of there being no relationship between variable and response. For women however, age provided another node at 70 years, inferring that women over 70 years perform poorer than those at 70 years or less. The lack of predictive variables in men might indicate a power-problem reflecting on the small number of male participants. However, one could also argue that the findings reflect the role of hippocampus in verbal memory. We found a slightly positive relationship between hippocampal volume and CVLT-score, which is in concordance with Walhovd et al., who found a correlation between CVLT free recall after 11 weeks, but not after 5 minutes [
54]. As also found, the size of the hippocampus declines by about 0.03 mL/year in both men and women, and given the smaller overall hippocampal volume in women, this would indicate a more prudent role for hippocampal volume in verbal memory in women.
We also found that APOE genotype did not have any important predictive value regarding CVLT-LD score. This was also confirmed by the more simple Wilcoxon rank sum test. This result is in accordance with Smith et al. [
10], who reported that the phenotypical significance of ApoEϵ4 seems to apply only in patients with diagnosed MCI or AD, but not in healthy controls [
55,
56]. However, others [
11,
12] have reported lower CVLT-LD scores in healthy elderly ApoEϵ4-positive individuals, suggesting that ApoEϵ4-related memory changes precede a clinical MCI or AD diagnosis.
The role of left hippocampal volume in verbal memory function has been reported in several previous studies [
57‐
61], but the exact contribution of this structure in relation to ApoEϵ4-zygosity is still unclear. Hippocampal volumes have, in most cases, been reported second to ApoEϵ4-zygosity in importance at follow-up, or of no importance at all at baseline measurement [
23]. It is remarkable that in our sample, the role of ApoEϵ4-zygosity, but also age, is negligible compared to that of left hippocampal volume in predicting verbal memory performance. This suggests a prominent role for the left hippocampal volume in the hierarchy of predictors to verbal memory function. Furthermore, since our analysis did not reveal any significant associations between hippocampal volumes and ApoEϵ4-zygosity, our investigation does not support the notion that changes in hippocampal volumes are, in fact, results of APOE genotype. The lack of findings relating to the APOE genotype may reflect our sample, consisting of healthy, rather well-functioning men and women. If one were to expand the "normality" criteria to include more subjects, one might find stronger APOE genotype correlations.
One other finding was that the hippocampus volume declines relatively more than the cortical volume with age (Figure
3). This is contradictory to the common perception that the cortex is more prone to age related change than the hippocampus. However, due to the high age distribution in our material, we postulate that these findings reflect an accelerated hippocampal atrophy occuring in advanced age [
62,
63]. A weakness in our study is the small number of participants. A total of 170 subjects could be too low, and only make for weaker statistical inference than would a larger sample. The sample selected for this study was also found to be rather homogeneous, something which is reflected in the above-normal distribution of education, IQ, and the age range (Table
1). However, in the literature there are indications that the effects of several predictive factors are only surfacing in the older segment of the population [
36,
64], thus questioning the significance of including young people in studies of age-related disease. When comparing the results to other aging studies one should be cautious, considering the slightly younger age group in our sample. This age composition produces a smaller variance in cognitive function as compared to other aging studies. However, the selection criteria were motivated by the desire to include only healthy elderly people, and to allow for follow-up studies of the same participants, where cognitive decline, neurodegeneration, and morphological abnormalities are expected to occur on a larger scale.
A possible confounder in our study is the different scanners used to acquire the brain volumes. This is however, a substantial difficulty in multi-center studies, as various scanner vendors provide a wide range of models with different specifications such as field strength, gradient system, coils, and pulse sequence principles and parameters. This might not present as a problem in clinical practice, or when manual deliniations and segmentations are performed, whereas automated methods can be more sensitive to subtle differences in image properties [
39]. However, this apparent weakness in the study can also be considered as a strength, as it demonstrates the methodological robustness behind the results. The fact that we obtained similar findings in two independent samples (i.e the Oslo and the Bergen material), also in terms of e.g. hippocampal volumes and its lateralization, is a significant strength of our study.
The automated image segmentation method used is well proven, and correlates well with more conventional, but time-demanding and subjectivity-prone methods [
37,
38]. This particular set of algorithms also produce reliable results compared to other, freely available software packages [
39]. Multivariate methods based on conditional inference trees were applied in our analysis. These are rather novel methods in the applied statistical community [
51,
65], and have to a very little extent been used or known to the medical imaging and aging research community. However, such types of classification and regression trees (CART), e.g. [
66], can provide robust and easily interpretable results.
A follow up study will be required to further investigate our findings. Such a study will provide an opportunity to do follow-up analysis much like Tupler et al. [
23], and thereby make stronger inferences concerning predictive values from our variables. Furthermore, one would benefit from methodological improvements in magnetic resonance imaging and data-analysis made in recent years. It would therefore be interesting (and feasible) to acquire data with different MRI measurement techniques during the same imaging session, such as diffusion tensor imaging (DTI) and functional MRI (fMRI). Diffusion tensor imaging has given valuable biological information regarding 'white matter integrity' in age-related cognitive decline [
67,
68]. In addition, a particular kind of BOLD fMRI examination, called resting-state fMRI (RS-fMRI) or task-free fMRI, has shown to be sensitive to neuropsychological/neurodegenerative diseases, such as AD, in that appropriate analysis of such data can reveal a disruption in functional resting-networks in the brain. The RS-fMRI method has a genuine potential as a biomarker of disease and also as an early objective marker of treatment response, but needs to be further investigated [
69,
70].
Competing interests
The authors declare that they have no competing interests.
Authors' contributions
MY was involved in data preparation, morphometric analysis, statistical analysis, main author. AJL was involved in study design, supervisor, internal review. EW was involved in data collection, neuropsychological assessment, internal review. TE was involved in sata collection, neuropsychological assessment, internal review. HR was involved in APOE-genotyping, internal review. LTW was involved in data preparation, morphometric analysis, internal review. MA was involved in data collection, neuropsychological assessment, internal review. SA was involved in data processing, internal review. JTG was involved in data acquisition, internal review. AMF was involved in data processing, internal review. IR was the principal investigator of the main study in Oslo and Bergen, and participated in study design, internal review. AL was the project supervisor, and participated in MRI acquisition protocol design, statistical analysis, internal review.