Lin Zhuang

White matter integrity in mild cognitive impairment: A tract-based spatial statistics study

Mild cognitive impairment (MCI) as a clinical diagnosis has limited specificity, and identifying imaging biomarkers may improve its predictive validity as a pre-dementia syndrome. This study used diffusion tensor imaging (DTI) to detect white matter (WM) structural alterations in MCI and its subtypes, and aimed to examine if DTI can serve as a potential imaging marker of MCI. We studied 96 amnestic MCI (aMCI), 69 non-amnestic MCI (naMCI), and 252 cognitively normal (CN) controls. DTI was performed to measure fractional anisotropy (FA), and tract-based spatial statistics (TBSS) were applied to investigate the characteristics of WM changes in aMCI and naMCI. The diagnostic utility of DTI in distinguishing MCI from CN was further evaluated by using a binary logistic regression model. We found that FA was significantly reduced in aMCI and naMCI when compared with CN. For aMCI subjects, decreased FA was seen in the frontal, temporal, parietal, and occipital WM, together with several commissural, association, and projection fibres. The best discrimination between aMCI and controls was achieved by combining FA measures of the splenium of corpus callosum and crus of fornix, with accuracy of 74.8% (sensitivity 71.0%, specificity 76.2%). For naMCI subjects, WM abnormality was more anatomically widespread, but the temporal lobe WM was relatively spared. These results suggest that aMCI is best characterized by pathology consistent with early Alzheimers disease, whereas underlying pathology in naMCI is more heterogeneous, and DTI analysis of white matter structural integrity can serve as a potential biomarker of MCI and its subtypes.

Microstructural white matter changes in cognitively normal individuals at risk of amnestic MCI

Objective: Since Alzheimer disease (AD) is a slowly progressive disorder and its pathologic features are likely to be present for many years before symptoms become manifest, we investigated whether microstructural white matter changes similar to those identified in patients with AD can be detected in cognitively normal individuals without dementia destined to develop amnestic mild cognitive impairment (aMCI). Methods: We studied 193 cognitively normal individuals, of whom 173 remained cognitively stable (CN-stable) and 20 were diagnosed with aMCI (CN-aMCI converter) 2 years later. Structural MRI and diffusion tensor imaging were acquired at baseline to assess gray matter atrophy and microstructural white matter changes, respectively. Results: At baseline, compared with CN-stable, CN-aMCI converters had substantial reductions in white matter integrity in the precuneus, parahippocampal cingulum, parahippocampal gyrus white matter, and fornix. Other diffuse white matter changes were observed in the frontal, parietal, and subcortical regions, whereas gray matter structures were relatively intact. The fractional anisotropy (FA) values of the precuneus were found to be a predictor of conversion from cognitively normal to aMCI. In addition, the FA values of the left parahippocampal gyrus white matter were predictive of subsequent episodic memory decline. Conclusions: Microstructural white matter changes are present in cognitively normal individuals in the pre-aMCI stage, and may serve as a potential imaging marker of early AD-related brain changes.

Microstructural White Matter Changes, Not Hippocampal Atrophy, Detect Early Amnestic Mild Cognitive Impairment

Background 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. Methods 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. Results 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. Conclusions 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.

A longitudinal study of brain atrophy over two years in community-dwelling older individuals

Most previous neuroimaging studies of age-related brain structural changes in older individuals have been cross-sectional and/or restricted to clinical samples. The present study of 345 community-dwelling non-demented individuals aged 70-90years aimed to examine age-related brain volumetric changes over two years. T1-weighted magnetic resonance imaging scans were obtained at baseline and at 2-year follow-up and analyzed using the FMRIB Software Library and FreeSurfer to investigate cortical thickness and shape and volumetric changes of subcortical structures. The results showed significant atrophy across much of the cerebral cortex with bilateral transverse temporal regions shrinking the fastest. Atrophy was also found in a number of subcortical structures, including the CA1 and subiculum subfields of the hippocampus. In some regions, such as left and right entorhinal cortices, right hippocampus and right precentral area, the rate of atrophy increased with age. Our analysis also showed that rostral middle frontal regions were thicker bilaterally in older participants, which may indicate its ability to compensate for medial temporal lobe atrophy. Compared to men, women had thicker cortical regions but greater rates of cortical atrophy. Women also had smaller subcortical structures. A longer period of education was associated with greater thickness in a number of cortical regions. Our results suggest a pattern of brain atrophy with non-demented people that resembles a less extreme form of the changes associated with Alzheimers disease (AD).

Is Alzheimer's a disease of the white matter?

Purpose of review Alzheimers disease has long been primarily considered a disease of gray matter. However, convergent evidence has suggested that white matter abnormalities are also important components of Alzheimers disease. We undertook a review of the recent findings of Alzheimers disease related white matter aberrations identified in patients with Alzheimers disease and using in-vitro and in-vivo models, and discuss the potential causes of white matter damage in Alzheimers disease. In doing so, we aim to provide a renewed insight into white matter changes in Alzheimers disease and related dementias. Recent findings Neuroimaging studies have found that patients with preclinical Alzheimers disease have widespread white matter abnormalities at a stage similar to those reported in Alzheimers disease, whereas gray matter structures were relatively intact. In addition, demyelination of the white matter is reported to occur prior to the presence of amyloid-&bgr; plaques and neurofibrillary tangles in the presymptomatic stages of Alzheimers disease. Furthermore, in a mouse model of Alzheimers disease, axonal disease due to impaired axonal transport was shown to precede and drive downstream production and aggregation of amyloid &bgr; peptides. Summary White matter abnormalities not only represent an early neuropathological event in Alzheimers disease but may also play an important role in the pathogenesis and diagnosis of Alzheimers disease.

Automated detection of amnestic mild cognitive impairment in community-dwelling elderly adults: a combined spatial atrophy and white matter alteration approach.

Amnestic mild cognitive impairment (aMCI) is a syndrome widely considered to be prodromal Alzheimers disease. Accurate diagnosis of aMCI would enable earlier treatment, and could thus help minimize the prevalence of Alzheimers disease. The aim of the present study was to evaluate a magnetic resonance imaging-based automated classification schema for identifying aMCI. This was carried out in a sample of community-dwelling adults aged 70-90 years old: 79 with a clinical diagnosis of aMCI and 204 who were cognitively normal. Our schema was novel in using measures of both spatial atrophy, derived from T1-weighted images, and white matter alterations, assessed with diffusion tensor imaging (DTI) tract-based spatial statistics (TBSS). Subcortical volumetric features were extracted using a FreeSurfer-initialized Large Deformation Diffeomorphic Metric Mapping (FS+LDDMM) segmentation approach, and fractional anisotropy (FA) values obtained for white matter regions of interest. Features were ranked by their ability to discriminate between aMCI and normal cognition, and a support vector machine (SVM) selected an optimal feature subset that was used to train SVM classifiers. As evaluated via 10-fold cross-validation, the classification performance characteristics achieved by our schema were: accuracy, 71.09%; sensitivity, 51.96%; specificity, 78.40%; and area under the curve, 0.7003. Additionally, we identified numerous socio-demographic, lifestyle, health and other factors potentially implicated in the misclassification of individuals by our schema and those previously used by others. Given its high level of performance, our classification schema could facilitate the early detection of aMCI in community-dwelling elderly adults.

Abnormalities of the Fornix in Mild Cognitive Impairment are Related to Episodic Memory Loss

The fornix is a major efferent tract of the hippocampus, a structure critical for normal memory function. However, the role of structural degradation of the fornix in memory dysfunction in mild cognitive impairment (MCI) has remained unclear. We used diffusion tensor tractography to measure microstructural properties of the fornix and the corticospinal tract (CST), as a control tract, in 206 cognitively normal subjects, 76 amnestic MCI (aMCI) and 51 non-amnestic MCI (naMCI) subjects. Hippocampal volumes were measured using deformation-based morphometry. We found significant fractional anisotropy reductions in the left fornix and radial diffusivity (RD) increases in bilateral fornices in aMCI, but not in naMCI, compared with controls. No significant changes in the CST were found in aMCI subjects, but naMCI subjects showed significantly increased RD and axial diffusivity of the right CST, compared with controls. Increased left fornical RD measure was correlated with poor verbal memory performance in aMCI subjects. In addition, reduced microstructural integrity of the fornix was associated with hippocampal atrophy in aMCI. This study suggests that microstructural alteration of the fornix is a contributor to early episodic memory dysfunction in non-demented individuals.

Changes in mild cognitive impairment and its subtypes as seen on diffusion tensor imaging

BACKGROUND Previous studies using diffusion tensor imaging (DTI) have observed microstructural abnormalities in white matter regions in both Alzheimers disease and mild cognitive impairment (MCI). The aim of this work was to examine the abnormalities in white matter and subcortical regions of MCI and its subtypes in a large, community-dwelling older aged cohort. METHODS A community-based sample of 396 individuals without dementia underwent medical assessment, neuropsychiatric testing, and neuroimaging. Of these, 158 subjects were classified as MCI and 238 as cognitively normal (controls) based on international MCI consensus criteria. Regional fractional anisotropy (FA) and mean diffusivity (MD) measures were calculated from the DTI and compared between groups. The false discovery rate correction was applied for multiple testing. RESULTS Subjects with MCI did not have significant differences in FA compared with controls after correction for multiple testing, but had increased MD in the right putamen, right anterior limb of the internal capsule, genu and splenium of the corpus callosum, right posterior cingulate gyrus, left superior frontal gyrus, and right and left corona radiata. When compared with controls, changes in left anterior cingulate, left superior frontal gyrus, and right corona radiata were associated with amnestic MCI (aMCI), whereas changes in the right putamen, right anterior limb of the internal capsule, and the right corona radiata were associated with non-amnestic MCI (naMCI). On logistic regression, the FA values in the left superior gyrus and MD values in the anterior cingulate distinguished aMCI from naMCI. CONCLUSIONS MCI is associated with changes in white matter and subcortical regions as seen on DTI. Changes in some anterior brain regions distinguish aMCI from naMCI.

White matter integrity and late-life depression in community-dwelling individuals: diffusion tensor imaging study using tract-based spatial statistics

BACKGROUND Late-life depression has been associated with white matter changes in studies using the regions of interest approach. AIMS To investigate the cross-sectional and longitudinal relationship between white matter integrity and depression in community-dwelling individuals using diffusion tensor imaging with tract-based spatial statistics. METHOD The sample comprised 381 participants aged between 72 and 92 years who were assessed twice within 2 years. Depressive symptoms were measured with the Geriatric Depression Scale. Tract-based spatial statistics were applied to investigate white matter integrity in currently depressed v. non-depressed elderly people and in those with a history of depression v. no history of depression. The relationship between white matter integrity and development of depressive symptoms after 2 years were analysed with logistic regression. RESULTS Individuals with current depression had widespread white matter integrity reduction compared with non-depressed elderly people. Significant fractional anisotropy reductions were found in 45 brain areas with the most notable findings in the frontal lobe, association and projection fibres. A history of depression was not associated with reduced fractional anisotropy. White matter changes in the superior frontal gyrus, posterior thalamic radiation, superior longitudinal fasciculus and in the body of corpus callosum predicted depression at follow-up. CONCLUSIONS Reduced white matter integrity is associated with late-life depression and predicts future depressive symptoms whereas a history of depression is not related to white matter changes. Disruption to white matter integrity may be a biomarker to predict late-life depression.

Genetics of Microstructure of the Corpus Callosum in Older Adults

The current study sought to examine the relative influence of genetic and environmental factors on corpus callosum (CC) microstructure in a community sample of older adult twins. Analyses were undertaken in 284 healthy older twins (66% female; 79 MZ and 63 DZ pairs) from the Older Australian Twins Study. The average age of the sample was 69.82 (SD = 4.76) years. Brain imaging scans were collected and DTI measures were estimated for the whole CC as well as its five subregions. Parcellation of the CC was performed using Analyze. In addition, white matter lesion (WMLs) burden was estimated. Heritability and genetic correlation analyses were undertaken using the SOLAR software package. Age, sex, scanner, handedness and blood pressure were considered as covariates. Heritability (h2) analysis for the DTI metrics of whole CC, indicated significant h2 for fractional anisotropy (FA) (h2 = 0.56; p = 2.89×10−10), mean diffusivity (MD) (h2 = 0.52; p = 0.30×10−6), radial diffusivity (RD) (h2 = 0.49; p = 0.2×10−6) and axial diffusivity (AD) (h2 = 0.37; p = 8.15×10−5). We also performed bivariate genetic correlation analyses between (i) whole CC DTI measures and (ii) whole CC DTI measures with total brain WML burden. Across the DTI measures for the whole CC, MD and RD shared 84% of the common genetic variance, followed by MD- AD (77%), FA - RD (52%), RD - AD (37%) and FA – MD (11%). For total WMLs, significant genetic correlations indicated that there was 19% shared common genetic variance with whole CC MD, followed by CC RD (17%), CC AD (16%) and CC FA (5%). Our findings suggest that the CC microstructure is under moderate genetic control. There was also evidence of shared genetic factors between the CC DTI measures. In contrast, there was less shared genetic variance between WMLs and the CC DTI metrics, suggesting fewer common genetic variants.