The cholinergic system in mild cognitive impairment and Alzheimer's disease: an in vivo MRI and DTI study

MRI markers for mild cognitive impairment: comparisons between white matter integrity and gray matter volume measurements

The aim of the study was to evaluate the value of assessing white matter integrity using diffusion tensor imaging (DTI) for classification of mild cognitive impairment (MCI) and prediction of cognitive impairments in comparison to brain atrophy measurements using structural MRI. Fifty-one patients with MCI and 66 cognitive normal controls (CN) underwent DTI and T1-weighted structural MRI. DTI measures included fractional anisotropy (FA) and radial diffusivity (DR) from 20 predetermined regions-of-interest (ROIs) in the commissural, limbic and association tracts, which are thought to be involved in Alzheimer's disease; measures of regional gray matter (GM) volume included 21 ROIs in medial temporal lobe, parietal cortex, and subcortical regions. Significant group differences between MCI and CN were detected by each MRI modality: In particular, reduced FA was found in splenium, left isthmus cingulum and fornix; increased DR was found in splenium, left isthmus cingulum and bilateral uncinate fasciculi; reduced GM volume was found in bilateral hippocampi, left entorhinal cortex, right amygdala and bilateral thalamus; and thinner cortex was found in the left entorhinal cortex. Group classifications based on FA or DR was significant and better than classifications based on GM volume. Using either DR or FA together with GM volume improved classification accuracy. Furthermore, all three measures, FA, DR and GM volume were similarly accurate in predicting cognitive performance in MCI patients. Taken together, the results imply that DTI measures are as accurate as measures of GM volume in detecting brain alterations that are associated with cognitive impairment. Furthermore, a combination of DTI and structural MRI measurements improves classification accuracy.

Relevance of magnetic resonance imaging for early detection and diagnosis of Alzheimer disease

Hippocampus volumetry currently is the best-established imaging biomarker for AD. However, the effect of multicenter acquisition on measurements of hippocampus volume needs to be explicitly considered when it is applied in large clinical trials, for example by using mixed-effects models to take the clustering of data within centers into account. The marker needs further validation in respect of the underlying neurobiological substrate and potential confounds such as vascular disease, inflammation, hydrocephalus, and alcoholism, and with regard to clinical outcomes such as cognition but also to demographic and socioeconomic outcomes such as mortality and institutionalization. The use of hippocampus volumetry for risk stratification of predementia study samples will further increase with the availability of automated measurement approaches. An important step in this respect will be the development of a standard hippocampus tracing protocol that harmonizes the large range of presently available manual protocols. In the near future, regionally differentiated automated methods will become available together with an appropriate statistical model, such as multivariate analysis of deformation fields, or techniques such as cortical-thickness measurements that yield a meaningful metrics for the detection of treatment effects. More advanced imaging protocols, including DTI, DSI, and functional MRI, are presently being used in monocenter and first multicenter studies. In the future these techniques will be relevant for the risk stratification in phase IIa type studies (small proof-of-concept trials). By contrast, the application of the broader established structural imaging biomarkers, such as hippocampus volume, for risk stratification and as surrogate end point is already today part of many clinical trial protocols. However, clinical care will also be affected by these new technologies. Radiologic expert centers already offer “dementia screening” for well-off middle-aged people who undergo an MRI scan with subsequent automated, typically VBM-based analysis, and determination of z-score deviation from a matched control cohort. Next-generation scanner software will likely include radiologic expert systems for automated segmentation, deformation-based morphometry, and multivariate analysis of anatomic MRI scans for the detection of a typical AD pattern. As these developments will start to change medical practice, first for selected subject groups that can afford this type of screening but later eventually also for other cohorts, clinicians must become aware of the potentials and limitations of these technologies. It is decidedly unclear to date how a middle-aged cognitively intact subject with a seemingly AD-positive MRI scan should be clinically advised. There is no evidence for individual risk prediction and even less for specific treatments. Thus, the development of preclinical diagnostic imaging poses not only technical but also ethical problems that must be critically discussed on the basis of profound knowledge. From a neurobiological point of view, the main determinants of cognitive impairment in AD are the density of synapses and neurons in distributed cortical and subcortical networks. MRI-based measures of regional gray matter volume and associated multivariate analysis techniques of regional interactions of gray matter densities provide insight into the onset and temporal dynamics of cortical atrophy as a close proxy for regional neuronal loss and a basis of functional impairment in specific neuronal networks. From the clinical point of view, clinicians must bear in mind that patients do not suffer from hippocampus atrophy or disconnection but from memory impairment, and that dementia screening in asymptomatic subjects should not be used outside of clinical studies.

Longitudinal measures of cholinergic forebrain atrophy in the transition from healthy aging to Alzheimer's disease

Recent evidence from cross-sectional in vivo imaging studies suggests that atrophy of the cholinergic basal forebrain (BF) in Alzheimer's disease (AD) can be distinguished from normal age-related degeneration even at predementia stages of the disease. Longitudinal study designs are needed to specify the dynamics of BF degeneration in the transition from normal aging to AD. We applied recently developed techniques for in vivo volumetry of the BF to serial magnetic resonance imaging scans of 82 initially healthy elderly individuals (60-93 years) and 50 patients with very mild AD (Clinical Dementia Rating score = 0.5) that were clinically followed over an average of 3 ± 1.5 years. BF atrophy rates were found to be significantly higher than rates of global brain shrinkage even in cognitively stable healthy elderly individuals. Compared with healthy control subjects, very mild AD patients showed reduced BF volumes at baseline and increased volume loss over time. Atrophy of the BF was more pronounced in progressive patients compared with those that remained stable. The cholinergic BF undergoes disproportionate degeneration in the aging process, which is further increased by the presence of AD.

Diffusion-weighted magnetic resonance imaging detection of basal forebrain cholinergic degeneration in a mouse model

Loss of basal forebrain cholinergic neurons is an early and key feature of Alzheimer's disease, and magnetic resonance imaging (MRI) volumetric measurement of the basal forebrain has recently gained attention as a potential diagnostic tool for this condition. The aim of this study was to determine whether loss of basal forebrain cholinergic neurons underpins changes which can be detected through diffusion MRI using diffusion tensor imaging (DTI) and probabilistic tractography in a mouse model. To cause selective basal forebrain cholinergic degeneration, the toxin saporin conjugated to a p75 neurotrophin receptor antibody (mu-p75-SAP) was used. This resulted in ~25% loss of the basal forebrain cholinergic neurons and significant loss of terminal cholinergic projections in the hippocampus, as determined by histology. To test whether lesion of cholinergic neurons caused basal forebrain, hippocampal, or whole brain atrophy, we performed manual segmentation analysis, which revealed no significant atrophy in lesioned animals compared to controls (Rb-IgG-SAP). However, analysis by DTI of the basal forebrain area revealed a significant increase in fractional anisotropy (FA; +7.7%), mean diffusivity (MD; +6.1%), axial diffusivity (AD; +8.5%) and radial diffusivity (RD; +4.0%) in lesioned mice compared to control animals. These parameters strongly inversely correlated with the number of choline acetyl transferase-positive neurons, with FA showing the greatest association (r(2)=0.72), followed by MD (r(2)=0.64), AD (r(2)=0.64) and RD (r(2)=0.61). Moreover, probabilistic tractography analysis of the septo-hippocampal tracts originating from the basal forebrain revealed an increase in streamline MD (+5.1%) and RD (+4.3%) in lesioned mice. This study illustrates that moderate loss of basal forebrain cholinergic neurons (representing only a minor proportion of all septo-hippocampal axons) can be detected by measuring either DTI parameters of the basal forebrain nuclei or tractography parameters of the basal forebrain tracts. These findings provide increased support for using DTI and probabilistic tractography as non-invasive tools for diagnosing and/or monitoring the progression of conditions affecting the integrity of the basal forebrain cholinergic system in humans, including Alzheimer's disease.

Individual classification of mild cognitive impairment subtypes by support vector machine analysis of white matter DTI

BACKGROUND AND PURPOSE

MCI was recently subdivided into sd-aMCI, sd-fMCI, and md-aMCI. The current investigation aimed to discriminate between MCI subtypes by using DTI.

MATERIALS AND METHODS

Sixty-six prospective participants were included: 18 with sd-aMCI, 13 with sd-fMCI, and 35 with md-aMCI. Statistics included group comparisons using TBSS and individual classification using SVMs.

RESULTS

The group-level analysis revealed a decrease in FA in md-aMCI versus sd-aMCI in an extensive bilateral, right-dominant network, and a more pronounced reduction of FA in md-aMCI compared with sd-fMCI in right inferior fronto-occipital fasciculus and inferior longitudinal fasciculus. The comparison between sd-fMCI and sd-aMCI, as well as the analysis of the other diffusion parameters, yielded no significant group differences. The individual-level SVM analysis provided discrimination between the MCI subtypes with accuracies around 97%. The major limitation is the relatively small number of cases of MCI.

CONCLUSIONS

Our data show that, at the group level, the md-aMCI subgroup has the most pronounced damage in white matter integrity. Individually, SVM analysis of white matter FA provided highly accurate classification of MCI subtypes.

Atrophy of the cholinergic Basal forebrain over the adult age range and in early stages of Alzheimer's disease

BACKGROUND

The basal forebrain cholinergic system (BFCS) is known to undergo moderate neurodegenerative changes during normal aging as well as severe atrophy in Alzheimer's disease (AD). However, there is a controversy regarding how the cholinergic lesion in AD relates to early and incipient stages of the disease. In vivo imaging studies on the structural integrity of the BFCS in normal and pathologic aging are rare.

METHODS

We applied automated morphometry techniques in combination with high-dimensional image warping and a cytoarchitectonic map of basal forebrain cholinergic nuclei to a large cross-sectional data set of high-resolution magnetic resonance imaging scans, covering the whole adult age range (20-94 years; n = 211) as well as patients with very mild AD (Clinical Dementia Rating = .5; n = 69) and clinically manifest AD (AD; Clinical Dementia Rating = 1; n = 28). For comparison, we investigated hippocampus volume using automated volumetry.

RESULTS

Volume of the BFCS declined from early adulthood on, and atrophy aggravated in advanced age. Volume reductions in very mild AD were most pronounced in posterior parts of the nucleus basalis of Meynert, whereas in AD, atrophy was more extensive and included the whole BFCS. In clinically manifest AD, the diagnostic accuracy of BFCS volume reached the diagnostic accuracy of hippocampus volume.

CONCLUSIONS

Our findings indicate that cholinergic degeneration in AD occurs against a background of age-related atrophy and that exacerbated atrophy in AD can be detected at earliest stages of cognitive impairment. Automated in vivo morphometry of the BFCS may become a useful tool to assess BF cholinergic degeneration in normal and pathologic aging.

The circadian clock and pathology of the ageing brain

Ageing leads to a functional deterioration of many brain systems, including the circadian clock--an internal time-keeping system that generates ∼24-hour rhythms in physiology and behaviour. Numerous clinical studies have established a direct correlation between abnormal circadian clock functions and the severity of neurodegenerative and sleep disorders. Latest data from experiments in model organisms, gene expression studies and clinical trials imply that dysfunctions of the circadian clock contribute to ageing and age-associated pathologies, thereby suggesting a functional link between the circadian clock and age-associated decline of brain functions. Potential molecular mechanisms underlying this link include the circadian control of physiological processes such as brain metabolism, reactive oxygen species homeostasis, hormone secretion, autophagy and stem cell proliferation.

Using support vector machines with multiple indices of diffusion for automated classification of mild cognitive impairment

Few studies have looked at the potential of using diffusion tensor imaging (DTI) in conjunction with machine learning algorithms in order to automate the classification of healthy older subjects and subjects with mild cognitive impairment (MCI). Here we apply DTI to 40 healthy older subjects and 33 MCI subjects in order to derive values for multiple indices of diffusion within the white matter voxels of each subject. DTI measures were then used together with support vector machines (SVMs) to classify control and MCI subjects. Greater than 90% sensitivity and specificity was achieved using this method, demonstrating the potential of a joint DTI and SVM pipeline for fast, objective classification of healthy older and MCI subjects. Such tools may be useful for large scale drug trials in Alzheimer's disease where the early identification of subjects with MCI is critical.

Resting state cortical electroencephalographic rhythms are related to gray matter volume in subjects with mild cognitive impairment and Alzheimer's disease

Cortical gray matter volume and resting state cortical electroencephalographic rhythms are typically abnormal in subjects with amnesic mild cognitive impairment (MCI) and Alzheimer's disease (AD). Here we tested the hypothesis that in amnesic MCI and AD subjects, abnormalities of EEG rhythms are a functional reflection of cortical atrophy across the disease. Eyes-closed resting state EEG data were recorded in 57 healthy elderly (Nold), 102 amnesic MCI, and 108 AD patients. Cortical gray matter volume was indexed by magnetic resonance imaging recorded in the MCI and AD subjects according to Alzheimer's disease neuroimaging initiative project (http://www.adni-info.org/). EEG rhythms of interest were delta (2-4 Hz), theta (4-8 Hz), alpha1 (8-10.5 Hz), alpha2 (10.5-13 Hz), beta1 (13-20 Hz), beta2 (20-30 Hz), and gamma (30-40 Hz). These rhythms were indexed by LORETA. Compared with the Nold, the MCI showed a decrease in amplitude of alpha 1 sources. With respect to the Nold and MCI, the AD showed an amplitude increase of delta sources, along with a strong amplitude reduction of alpha 1 sources. In the MCI and AD subjects as a whole group, the lower the cortical gray matter volume, the higher the delta sources, the lower the alpha 1 sources. The better the score to cognitive tests the higher the gray matter volume, the lower the pathological delta sources, and the higher the alpha sources. These results suggest that in amnesic MCI and AD subjects, abnormalities of resting state cortical EEG rhythms are not epiphenomena but are strictly related to neurodegeneration (atrophy of cortical gray matter) and cognition.

Multicenter stability of diffusion tensor imaging measures: a European clinical and physical phantom study

Diffusion tensor imaging (DTI) detects white matter damage in neuro-psychiatric disorders, but data on reliability of DTI measures across more than two scanners are still missing. In this study we assessed multicenter reproducibility of DTI acquisitions based on a physical phantom as well as brain scans across 16 scanners. In addition, we performed DTI scans in a group of 26 patients with clinically probable Alzheimer's disease (AD) and 12 healthy elderly controls at one single center. We determined the variability of fractional anisotropy (FA) measures using manually placed regions of interest as well as automated tract based spatial statistics and deformation based analysis. The coefficient of variation (CV) of FA was 6.9% for the physical phantom data. The mean CV across the multicenter brain scans was 14% for tract based statistics, and 29% for deformation based analysis. The degree of variation was higher in less organized fiber tracts. Our findings suggest that a clinical and physical phantom study involving more than two scanners is indispensable to detect potential sources of bias and to reliably estimate effect size in multicenter diagnostic trials using DTI.

Parasympathetic autonomic dysfunction is common in mild cognitive impairment

Components of the central autonomic network attract the greatest neurofibrillary degeneration and related cell death during the course of Alzheimer's disease (AD). The insular cortex and brainstem are affected from the early stages of disease. Acetylcholine, the main neurotransmitter of the parasympathetic system may be deficient in mild cognitive impairment (MCI). Hence, autonomic dysfunction may be a novel biomarker of neurodegeneration. Autonomic function was examined in 97 MCI participants and 36 controls using beside cardiovascular reflex tests and heart rate variability. The association between dysautonomia and neuropsychiatric deficits was examined. This observational study was conducted in a clinical setting. MCI participants showed significant parasympathetic deficits in bedside cardiovascular reflex tests and heart rate variability compared with controls. Those with more significant autonomic dysfunction had more severe neuropsychological deficits. MCI participants were 5.60 (95% confidence interval, 1.6-27.2) times more likely than a control to have autonomic dysfunction. Autonomic dysfunction, particularly parasympathetic dysfunction is prevalent in MCI. This may be due to early neuroanatomical and neurochemical changes in the central autonomic network in Alzheimer's disease. This may accelerate cognitive decline via proinflammatory mechanisms and/or hypotension-induced cerebral hypoperfusion. This provides insight into the pathophysiological mechanisms that contribute to cognitive decline, and may lead to the development of effective therapeutic interventions.

Staging Alzheimer's disease progression with multimodality neuroimaging

Rapid developments in medical neuroimaging have made it possible to reconstruct the trajectory of Alzheimer's disease (AD) as it spreads through the living brain. The current review focuses on the progressive signature of brain changes throughout the different stages of AD. We integrate recent findings on changes in cortical gray matter volume, white matter fiber tracts, neuropathological alterations, and brain metabolism assessed with molecular positron emission tomography (PET). Neurofibrillary tangles accumulate first in transentorhinal and cholinergic brain areas, and 4-D maps of cortical volume changes show early progressive temporo-parietal cortical thinning. Findings from diffusion tensor imaging (DTI) for assessment fiber tract integrity show cortical disconnection in corresponding brain networks. Importantly, the developmental trajectory of brain changes is not uniform and may be modulated by several factors such as onset of disease mechanisms, risk-associated and protective genes, converging comorbidity, and individual brain reserve. There is a general agreement between in vivo brain maps of cortical atrophy and amyloid pathology assessed through PET, reminiscent of post mortem histopathology studies that paved the way in the staging of AD. The association between in vivo and post mortem findings will clarify the temporal dynamics of pathophysiological alterations in the development of preclinical AD. This will be important in designing effective treatments that target specific underlying disease AD mechanisms.

Brazilian psychiatric brain bank: a new contribution tool to network studies

There is an urgent need for expanding the number of brain banks serving psychiatric research. We describe here the Psychiatric Disorders arm of the Brain Bank of the Brazilian Aging Brain Study Group (Psy-BBBABSG), which is focused in bipolar disorder (BD) and obsessive compulsive disorder (OCD). Our protocol was designed to minimize limitations faced by previous initiatives, and to enable design-based neurostereological analyses. The Psy-BBBABSG first milestone is the collection of 10 brains each of BD and OCD patients, and matched controls. The brains are sourced from a population-based autopsy service. The clinical and psychiatric assessments were done by an expert team including psychiatrists, through an informant. One hemisphere was perfused-fixed to render an optimal fixation for conducting neurostereological studies. The other hemisphere was comprehensively dissected and frozen for molecular studies. In 20 months, we collected 36 brains. A final report was completed for 14 cases: 3 BDs, 4 major depressive disorders, 1 substance use disorder, 1 mood disorder NOS, 3 obsessive compulsive spectrum symptoms, 1 OCD and 1 schizophrenia. The majority were male (64%), and the average age at death was 67.2 ± 9.0 years. The average postmortem interval was 16 h. Three matched controls were collected. The pilot stage confirmed that the protocols are well fitted to reach our goals. Our unique autopsy source makes possible to collect a fairly number of high quality cases in a short time. Such a collection offers an additional to the international research community to advance the understanding on neuropsychiatric diseases.