The authors have declared that no competing interests exist.
Conceived and designed the experiments: LZ WW. Performed the experiments: LZ. Analyzed the data: LZ. Contributed reagents/materials/analysis tools: LZ WW PS JT SR NK HB. Wrote the paper: LZ.
Alzheimer’s disease (AD) is generally considered to be characterized by pathology in gray matter of the brain, but convergent evidence suggests that white matter degradation also plays a vital role in its pathogenesis. The evolution of white matter deterioration and its relationship with gray matter atrophy remains elusive in amnestic mild cognitive impairment (aMCI), a prodromal stage of AD.
We studied 155 cognitively normal (CN) and 27 ‘late’ aMCI individuals with stable diagnosis over 2 years, and 39 ‘early’ aMCI individuals who had converted from CN to aMCI at 2-year follow up. Diffusion tensor imaging (DTI) tractography was used to reconstruct six white matter tracts three limbic tracts critical for episodic memory function - the fornix, the parahippocampal cingulum, and the uncinate fasciculus; two cortico-cortical association fiber tracts - superior longitudinal fasciculus and inferior longitudinal fasciculus; and one projection fiber tract - corticospinal tract. Microstructural integrity as measured by fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD) and axial diffusivity (AxD) was assessed for these tracts.
Compared with CN, late aMCI had lower white matter integrity in the fornix, the parahippocampal cingulum, and the uncinate fasciculus, while early aMCI showed white matter damage in the fornix. In addition, fornical measures were correlated with hippocampal atrophy in late aMCI, whereas abnormality of the fornix in early aMCI occurred in the absence of hippocampal atrophy and did not correlate with hippocampal volumes.
Limbic white matter tracts are preferentially affected in the early stages of cognitive dysfunction. Microstructural degradation of the fornix preceding hippocampal atrophy may serve as a novel imaging marker for aMCI at an early stage.
As Alzheimer’s disease (AD) is a progressive neurological condition, identifying changes early in the disease process is of clinical importance to enable early diagnosis and intervention. The construct of mild cognitive impairment (MCI) captures the earliest clinical features of dementia, and may be an appropriate stage for clinical enquiry
Gray matter (GM) atrophy is a prominent feature of aMCI, with the hippocampus being the earliest and most vulnerable region to become affected
Previous studies using diffusion tensor imaging (DTI) fiber tractography have found decreased microstructural integrity of major WM tracts in aMCI, but the results varied considerably across these studies. For instance, one study reported compromised fornix WM integrity and unchanged parahippocampal cingulum
To examine WM tract degeneration and its relationship with GM atrophy in prodromal stages of AD, this study measured WM integrity and hippocampal volumes at two stages of aMCI – those who recently converted to aMCI from normal cognition previously, and those who had received the diagnosis of aMCI for at least two years. DTI tractography was used to examine three limbic WM tracts (the fornix, the parahippocampal cingulum, and the uncinate fasciculus), two cortico-cortical association WM tracts (the superior longitudinal fasciculus and the inferior longitudinal fasciculus) and one projection fiber tract comprising the corticospinal tract. Given the functional importance of the three limbic WM tracts in episodic memory
Written informed consent was obtained from each participant. The study was approved by the Ethics Committees of the University of New South Wales and the South Eastern Sydney and Illawarra Area Health Service and was in accordance with the Declaration of Helsinki.
All participants were recruited from the Sydney Memory and Ageing Study (MAS), a population-based longitudinal study of non-demented older people aged 70–90 in Sydney, Australia. Participants were excluded if they had a history of dementia, schizophrenia, bipolar disorder, multiple sclerosis, motor neuron disease, developmental disability, progressive malignancy, a Mini-Mental State Examination (MMSE) <24 adjusted for age and education, insufficient English language abilities to complete assessment, or any medical or psychological conditions that might interfere with clinical and neuropsychological assessment.
Participants in the present study, who were assessed at two waves, two years apart, were 155 cognitively normal (CN) individuals (age range, 72.47 to 90.47 yrs) who were cognitively normal at both waves, 27 ‘late’ aMCI subjects (age range, 74.05 to 88.81 yrs) who were cognitively impaired in the memory domain at both waves, and 39 ‘early’ aMCI subjects (age range, 72.95 to 90.72 yrs) who were cognitively normal at wave 1 and diagnosed with aMCI at wave 2. Details of the demographic profiles of all participants are provided in
CN | Late aMCI | Early aMCI | F | p value | |
Mean ± SD | Mean ± SD | Mean ± SD | |||
Age (years) | 79.08±4.36 | 81.01±4.60 | 80.74±5.29 | 3.506 | 0.032 |
Sex (M/F) | 61/94 | 18/9 | 24/15 | 11.136 | 0.004 |
Education (years) | 11.99±3.65 | 12.28±4.15 | 13.00±4.37 | 1.072 | 0.344 |
Episodic memory | 0.221±0.944 | −2.216±0.845 | −1.356±1.103 | 92.236 | <0.001a |
APOE4,+/1 | 33/122 | 9/18 | 7/32 | 2.422 | 0.298 |
WMHs (percent ICV) | 0.991±0.948 | 1.109±0.753 | 0.927±0.751 | 0.346 | 0.708 |
Left HV mm3Right HV mm3 | 3591±4393351±420 | 3370±5293187±455 | 3564±5003344±433 | 4.0752.917 | 0.018a |
CN, cognitively normal; aMCI, amnestic mild cognitive impairment; WMHs, white matter hyperintensities; HV, hippocampal volume.
significant difference between late aMCI and cognitively normal controls.
significant difference between early aMCI and cognitively normal controls.
significant difference between late aMCI and early aMCI.
Significance at p<0.05.
Significance at P<0.001.
Diagnosis of MCI was made based on the recent international consensus criteria
The MRI scans used in the current study are from the second wave of the MAS study beginning in Oct 2007 and finishing in Dec 2009. All subjects underwent MRI scanning on a Philips 3T Achieva Quasar Dual MRI scanner (Philips Medical System, Best, The Netherlands) located at Neuroscience Research Australia (NeuRA), Sydney, Australia. For each participant, the MRI scan was obtained within 3 months after the neuropsychological testing. 32 directional DTI data (b = 1000 s/mm2) with three no-diffusion weighted b0 images were acquired with a single-shot, spin-echo, echo-planar imaging (EPI) sequence: echo time (TE) = 68 ms, repetition time (TR) = 7767 ms, flip angle = 90°, matrix size = 240×240, field of view (FOV) = 240×240 mm, yielding in-plane resolution of 1×1 mm, 55 2.5 mm contiguous axial slices without gap. Each DTI scan was repeated twice to increase the signal to noise ratio (SNR). High-resolution T1-weighted structural images were acquired for hippocampal volumetry analysis using turbo field echo sequence with the following protocols: TE = 2.61 ms, TR = 5.75 ms, flip angle = 8°, FOV = 256×256×190 mm, 1 mm slice thickness with no gap, voxel size = 1×1×1 mm3. T2-FLAIR was acquired with TR = 10000 ms, TE = 110 ms, matrix size = 512×512, slice thickness = 3.5 mm without gap, and in plane resolution = 0.488×0.488 mm.
DTI data were pre-processed and analysed with the FMRIB’s Diffusion Toolbox (FDT) of the FMRIB’s Software Library (FSL) version 4.1.7 (
Fiber tractography was performed for each subject in the diffusion space to delineate fiber tracts using a probabilistic crossing-fiber tracking algorithm implemented within the FDT toolbox of the FSL software. Prior to running fiber tracking, Bayesian Estimation of Diffusion Parameters (BEDPOSTX) using Markov Chain Monte Carlo sampling was conducted on the output of eddy-current corrected DTI data to generate distributions of diffusion parameters and model crossing fibers at each image voxel. After applying BEDPOSTX to eddy-current corrected DTI data, fiber tracking was initiated with 5000 streamline samples from all voxels within the seed mask to create a connectivity distribution of each fiber tract in the original diffusion space. The output fiber connectivity map contained a connectivity value at each voxel, representing the number of streamlines projecting from the seed region and passing through the waypoint mask. In order to remove image noise, each fiber connectivity image was then thresholded to include only voxels with a connectivity value of 20% of the maximum connectivity value or more. The thresholded fiber connectivity map was binarized to create a mask of each fiber tract. Then, mean FA and MD values were calculated within the mask of the corresponding fiber tract in the diffusion space. In addition, probability maps of six WM tracts were created to check the anatomical consistency of the same tract across all subjects (
All tracts were superimposed on the MNI T1 template. Only voxels present in at least 10% of the study participants are shown in red-yellow. The colour bar denotes the percentage of subjects in whom the reconstructed fiber tract exists.
All tracts were overlaid on a 3D rendering of the MNI T1 template.
A two-ROI approach was applied to draw seed and waypoint ROIs on the colour-coded FA map of each subject to isolate specific fiber tracts. These ROIs were manually placed by a single rater (L.Z) blind to clinical information, based on a previously published protocol
WM hyperintensities (WMHs) for each subject were extracted using our in-house software
WMHs were shown in the red-yellow and superimposed on the MNI T1 template. The color bar denotes the percentage of subjects who had WMHs in each image voxel.
Automated segmentation of bilateral hippocampi was performed using the FMRIB’s Integrated Registration and Segmentation Tool (FIRST)
One-way analysis of variance (ANOVA) was performed to test the group difference in continuous variables of demographic and neuropsychological data, and categorical data were compared using Pearson’s Chi-square test. Analyses of covariance (ANCOVAs) with Bonferroni adjustment for multiple comparisons were performed to assess the group difference in DTI, WMHs and hippocampal volumetric measures, while including age, sex, years of education and APOE genotype as covariates of no interest. DTI measures of WM tracts showing significant between group differences were then entered into a series of stepwise linear regression models as dependent variables, while including WMHs, hippocampal volume, age, sex, years of education, and APOE genotype as independent variables to determine which variable was most predictive of WM changes in early and late aMCI. All statistical analyses were performed using the PASW software package version 18 (SPSS, Inc., Chicago, IL, USA).
As shown in
After correcting for age, sex, years of education and ICV, there were no significant differences among the three diagnostic groups in total WMHs burden. Left hippocampal volumes were significantly different among the three groups whereas right hippocampal volumes were not. Post-hoc analysis showed that the left hippocampus was significantly atrophic in late aMCI subjects (p = 0.016) compared with controls. No significant differences in the hippocampal volume were found between early and late aMCI, or between early aMCI and controls.
FA and MD values of the three groups are shown in
CN | Early aMCI | Late aMCI | F (p value) | Early aMCI vs. Late aMCI | Early aMCI vs. CN | Late aMCI vs. CN | |
Mean (SD) | Mean (SD) | Mean (SD) | |||||
Fx L FA | 0.320 (0.027) | 0.307 (0.023) | 0.298 (0.032) | 5.542 (0.005) | 0.661 | 0.177 | 0.007 |
Fx R FA | 0.324 (0.028) | 0.310(0.024) | 0.305 (0.034) | 4.552 (0.012) | 1.000 | 0.127 | 0.030 |
Fx L MD(mm2/s) | 1.493 (0.142) | 1.600 (0.112) | 1.600 (0.123) | 7.002 (0.001) | 1.000 | 0.005 |
0.030 |
Fx R MD(mm2/s) | 1.485 (0.142) | 1.597 (0.120) | 1.593 (0.128) | 7.846 (0.001) | 1.000 | 0.002 |
0.027 |
UF L MD(mm2/s) | 0.871 (0.057) | 0.884 (0.086) | 0.931 (0.084) | 7.172 (0.001) | 0.017 |
1.000 | 0.001 |
UF R MD(mm2/s) | 0.830 (0.047) | 0.839 (0.058) | 0.871 (0.052) | 6.706 (0.001) | 0.032 |
1.000 | 0.001 |
PHC L MD(mm2/s) | 0.849 (0.046) | 0.857 (0.048) | 0.884 (0.074) | 3.948 (0.021) | 0.074 | 1.000 | 0.018 |
Abbreviation: PHC, parahippocampal cingulum; Fx, fornix; UF, uncinate fasciculus; ILF, inferior longitudinal fasciculus; SLF, superior longitudinal fasciculus; CST, corticospinal tract. aMCI, amnestic mild cognitive impairment; CN, cognitively normal; L, left; R, right.
Significance at p<0.05.
Significance at P<0.01.
As shown in
Left Fx FA |
Right Fx FA |
Left Fx MD |
Right Fx MD |
Left UF MD |
Right UF MD |
Left PHC MD |
Left Fx MD |
Right Fx MD |
|
Beta (p value) | Beta (p value) | Beta (p value) | Beta (p value) | Beta (p value) | Beta (p value) | Beta (p value) | Beta (p value) | Beta (p value) | |
Age | −0.156(0.473) | −0.202(0.379) | −0.058(0.801) | 0.100(0.672) | 0.021(0.917) | 0.452(0.034) | 0.164(0.453) | 0.153(0.393) | 0.147(0.431) |
Sex | −0.117(0.576) | −0.219(0.326) | 0.054(0.807) | 0.011(0.962) | 0.200(0.320) | 0.235(0.236) | 0.151(0.473) | −0212(0.302) | −0.301(0.163) |
Education | −0.026(0.905) | −0.088(0.712) | 0.199(0.405) | 0.116(0.641) | 0.196(0.361) | 0.018(0.932) | −0.008(0.971) | 0.113(0.605) | −0.028(0.904) |
APOEε4 | −0.105(0.621) | −0.198(0.377) | 0.061(0.788) | 0.059(0.798) | 0.160(0.432) | 0.095(0.629) | 0.254(0.241) | −0.196(0.304) | −0.089(0.635) |
WMHs | −0.052(0.794) | −0.188(0.368) | 0.232(0.277) | 0.317(0.152) | 0.059(0.754) | −0.035(0.849) | 0.061(0.757) | 0.136(0.505) | 0.128(0.546) |
Left HV | 0.594(0.008) | N/A | −0.413(0.066) | N/A | −0.569(0.007) | N/A | −0.545(0.013) | −0.299(0.136) | N/A |
Right HV | N/A | 0.393(0.078) | N/A | −0.364(0.144) | N/A | −2.632(0.017) | N/A | N/A | −0.062(0.758) |
Abbreviation: PHC, parahippocampal cingulum; Fx, fornix; UF, uncinate fasciculus; WMHs, white matter hyperintensities; HV, hippocampal volume; FA, fractional anisotropy; MD, mean diffusivity.
the late aMCI group.
the early aMCI group.
Regression analysis showed that episodic memory performance was significantly associated with left parahippocampal cingulum MD, fornical FA bilaterally, fornical MD bilaterally, and left uncinate fasciculus, as well as left normalized hippocampal volumes. When all these anatomic structures were entered simultaneously into a single regression model, only left parahippocampal cingulum MD remained as a significant predictor of episodic memory performance (β = −0.173, t = −2.330, p = 0.021).
This study characterized WM microstructural injury and its relation to hippocampal atrophy at different stages of aMCI. We found that late aMCI individuals with severe memory deficits had significant microstructural WM abnormalities in the limbic WM tracts including the fornices bilaterally, the uncinate fasciculus bilaterally, and the left parahippocampal cingulum, compared with controls. In addition, hippocampal atrophy was found in late aMCI and correlated with DTI measures of limbic WM tracts. In contrast, early aMCI individuals with mild memory impairment demonstrated less severe WM tract damage with only bilateral fornices involved, while the hippocampus was still intact and did not associate with DTI measures of the fornix in early aMCI.
A previous DTI study using the region of interest method found that the fornix was more severely affected than the parahippocampal cingulum and left orbitofrontal WM in presymptomatic familial AD genetic mutation carriers who were destined to develop AD
Significant MD increases and unchanged FA were found in early aMCI, which is consistent with previous studies
WM damage in AD and MCI is generally considered to be a consequence of Wallerian degeneration secondary to cell loss in the GM. Since the fornix has axonal connections with the cellular layer of the subiculum, which is a primary site of substantial neuronal loss within the hippocampus
Two recent DTI studies found that fornical damage was independent of hippocampal atrophy in APOE4 carriers before the onset of cognitive impairment
The etiology of this ‘primary’ WM degeneration in the fornix remains unclear. Small vessel disease is common in the elderly and may be the likely explanation for the WM changes. Since the frontal-subcortical circuits are the earliest and most vulnerable region to be affected by vascular pathology, the early clinical symptom of vascular disease is not memory decline, however. Although previous studies have reported ischaemia of the fornix, it only occurs in extremely rare circumstances
We would like to consider the alternative possibility that the early change in WM seen in our aMCI subjects is primarily degenerative. The APOE4 allele, a well-established genetic risk factor for AD, has been linked to WM deficits in the brain regions selectively vulnerable to AD-related pathology
Animal model studies
There were some limitations in the present study. First, the cross sectional nature of the analysis, even though the subjects were assessed over two waves, limited its ability to detect longitudinal changes of WM tracts. Second, it lacked amyloid imaging and histopathological data suggestive of AD pathology in aMCI subjects, thereby relying on clinical diagnosis only. Ongoing longitudinal follow-up will assess the proportion of aMCI subjects who will eventually convert to AD. Third, although the functional significance of limbic WM tracts in episodic memory was identified, the role of these fiber tracts in the encoding and retrieval components of episodic memory warrants further research. Fourth, the study did not evaluate other WM tracts critical for episodic memory, such as the mammillothalamic tract, which is too small to be reconstructed by the current DTI technique. Ultra-high resolution DTI is required to achieve a better understanding of WM tract damage in the early phase of prodromal AD. Despite these limitations, the present study demonstrated distinct patterns of WM tract abnormalities at different stages of aMCI, providing further insight into the temporal order of WM degeneration in prodromal AD.
Group comparisons of AxD and RD measures in early aMCI, late aMCI, and controls. Abbreviation: PHC, parahippocampal cingulum; Fx, fornix; UF, uncinate fasciculus; ILF, inferior longitudinal fasciculus; SLF, superior longitudinal fasciculus; CST, corticospinal tract. aMCI, amnestic mild cognitive impairment; CN, cognitively normal; L, left; R, right.
(DOCX)
The authors thank the study participants and interviewers, as well the Sydney Memory and Ageing Study team. We also thank Kate Crosbie for her assistance with manuscript preparation.