Objective

To characterize the shape of the trajectories of Alzheimer’s Disease (AD) biomarkers as a function of MMSE.

Design

Longitudinal registries from the Mayo Clinic and the Alzheimer’s Disease Neuroimaging Initiative (ADNI).

Patients

Two different samples (n=343 and n=598) were created that spanned the cognitive spectrum from normal to AD dementia. Subgroup analyses were performed in members of both cohorts (n=243 and n=328) who were amyloid positive at baseline.

Main Outcome Measures

The shape of biomarker trajectories as a function of MMSE, adjusted for age, was modeled and described as baseline (cross-sectional) and within-subject longitudinal effects. Biomarkers evaluated were cerebro spinal fluid (CSF) Aβ42 and tau; amyloid and fluoro deoxyglucose position emission tomography (PET) imaging, and structural magnetic resonance imaging (MRI).

Results

Baseline biomarker values generally worsened (i.e., non-zero slope) with lower baseline MMSE. Baseline hippocampal volume, amyloid PET and FDG PET values plateaued (i.e., non-linear slope) with lower MMSE in one or more analyses. Longitudinally, within-subject rates of biomarker change were associated with worsening MMSE. Non-constant within-subject rates (deceleration) of biomarker change were found in only one model.

Conclusions

Biomarker trajectory shapes by MMSE were complex and were affected by interactions with age and APOE status. Non-linearity was found in several baseline effects models. Non-constant within-subject rates of biomarker change were found in only one model, likely due to limited within-subject longitudinal follow up. Creating reliable models that describe the full trajectories of AD biomarkers will require significant additional longitudinal data in individual participants.

Objective

A workgroup commissioned by the Alzheimer’s Association (AA) and the National Institute on Aging (NIA) recently published research criteria for preclinical Alzheimer’s disease (AD). We performed a preliminary assessment of these guidelines.

Methods

We employed Pittsburgh compound B positron emission tomography (PET) imaging as our biomarker of cerebral amyloidosis and 18fluorodeoxyglucose PET imaging and hippocampal volume as biomarkers of neurodegeneration. A group of 42 clinically diagnosed AD subjects was used to create imaging biomarker cut-points. A group of 450 cognitively normal (CN) subjects from a population based sample was used to develop cognitive cut-points and to assess population frequencies of the different preclinical AD stages using different cut-point criteria.

Results

The new criteria subdivide the preclinical phase of AD into stages 1–3. To classify our CN subjects, two additional categories were needed. Stage 0 denotes subjects with normal AD biomarkers and no evidence of subtle cognitive impairment. Suspected Non-AD Pathophysiology (SNAP) denotes subjects with normal amyloid PET imaging, but abnormal neurodegeneration biomarker studies. At fixed cut-points corresponding to 90% sensitivity for diagnosing AD and the 10th percentile of CN cognitive scores, 43% of our sample was classified as stage 0; 16% stage 1; 12 % stage 2; 3% stage 3; and 23% SNAP.

Interpretation

This cross-sectional evaluation of the NIA-AA criteria for preclinical AD indicates that the 1–3 staging criteria coupled with stage 0 and SNAP categories classify 97% of CN subjects from a population-based sample, leaving just 3% unclassified. Future longitudinal validation of the criteria will be important.

Background

Axonal damage and inflammatory demyelination both occur in multiple sclerosis (MS). Some studies suggest that statins, through pleiotropic effects, reduce inflammatory episodes and protect neurons. However, other studies suggest statins have disparate impacts on these pathologic processes.

Objective

To assess disability progression in MS patients receiving statin therapy.

Methods

Retrospective medical record review of an established population-based MS prevalence cohort in Olmsted County, Minnesota, comparing disability progression between patients receiving statins and controls.

Results

Duration of statin use ranged from 1.9 to 20.3 years with a mean and standard deviation of 6.8 +/− 4 years. Years between assessments ranged from 0.6 to 8.2 (75% of patients having intervals >6.4 years). The median (interquartile range) absolute change of disability among the statin group was 0 (0 to +1), compared to +0.5 (0, +1) in the no-statin group. Distributions were not significantly different (P = 0.39). The mean (standard deviation) absolute change of disability scores among the statin group was +0.69 (+1.49), not significantly different from +0.61 (+1.31) in the no-statin group. Likewise, annualized disability scores did not differ significantly (P = 0.23). Eighteen (40%) patients worsened by 1.0 or more on EDSS in the statin group and 36 (40%) in the no-statin group (P = 0.85, chi-squared test).

Conclusions

In this cohort, disability progression did not differ between those receiving statin therapy and controls. These findings support the hypothesis that statins, in doses currently prescribed for hyperlipidemia, do not affect the long-term course of multiple sclerosis.

Objective

To empirically assess the concept that Alzheimer’s disease (AD) biomarkers significantly depart from normality in a temporally ordered manner.

Design

Validation sample

Setting

Multi-site, referral centers

Patients

We studied 401 elderly cognitively normal (CN), Mild Cognitive Impairment (MCI) and AD dementia subjects from the Alzheimer’s Disease Neuroimaging Initiative. We compared the proportions of three AD biomarkers – CSF Aβ42, CSF total tau (t-tau), and hippocampal volume adjusted by intra-cranial volume (HVa) - that were abnormal as cognitive impairment worsened. Cut-points demarcating normal vs. abnormal for each biomarker were established by maximizing diagnostic accuracy in independent autopsy samples.

Interventions

None

Main Outcome measures

AD biomarkers

Results

Within each clinical group in the entire sample (n=401) CSF Aβ42 was abnormal more often than t-tau or HVa. Among the 298 subjects with both baseline and 12 month data, the proportion of subjects with abnormal Aβ42 did not change from baseline to 12 months in any group. The proportion of subjects with abnormal t-tau increased from baseline to 12 months in CN (p=0.05) but not in MCI or dementia. In 209 subjects with abnormal CSF AB42 at baseline, the percent abnormal HVa, but not t-tau, increased from baseline to 12 months in MCI.

Conclusions

Reduction in CSF Aβ42 denotes a pathophysiological process that significantly departs from normality (i.e., becomes dynamic) early, while t-tau and HVa are biomarkers of downstream pathophysiological processes. T-tau becomes dynamic before HVa, but HVa is more dynamic in the clinically symptomatic MCI and dementia phases of the disease than t-tau.

BACKGROUND

Cortical disease has emerged as a critical aspect of the pathogenesis of multiple sclerosis, being associated with disease progression and cognitive impairment. Most studies of cortical lesions have focused on autopsy findings in patients with long-standing, chronic, progressive multiple sclerosis, and the noninflammatory nature of these lesions has been emphasized. Magnetic resonance imaging studies indicate that cortical damage occurs early in the disease.

METHODS

We evaluated the prevalence and character of demyelinating cortical lesions in patients with multiple sclerosis. Cortical tissues were obtained in passing during biopsy sampling of white-matter lesions. In most cases, biopsy was done with the use of stereotactic procedures to diagnose suspected tumors. Patients with sufficient cortex (138 of 563 patients screened) were evaluated for cortical demyelination. Using immunohistochemistry, we characterized cortical lesions with respect to demyelinating activity, inflammatory infiltrates, the presence of meningeal inflammation, and a topographic association between cortical demyelination and meningeal inflammation. Diagnoses were ascertained in a subgroup of 77 patients (56%) at the last follow-up visit (at a median of 3.5 years).

RESULTS

Cortical demyelination was present in 53 patients (38%) (104 lesions and 222 tissue blocks) and was absent in 85 patients (121 tissue blocks). Twenty-five patients with cortical demyelination had definite multiple sclerosis (81% of 31 patients who underwent long-term follow-up), as did 33 patients without cortical demyelination (72% of 46 patients who underwent long-term follow-up). In representative tissues, 58 of 71 lesions (82%) showed CD3+ T-cell infiltrates, and 32 of 78 lesions (41%) showed macrophage-associated demyelination. Meningeal inflammation was topographically associated with cortical demyelination in patients who had sufficient meningeal tissue for study.

CONCLUSIONS

In this cohort of patients with early-stage multiple sclerosis, cortical demyelinating lesions were frequent, inflammatory, and strongly associated with meningeal inflammation. (Funded by the National Multiple Sclerosis Society and the National Institutes of Health.)

Background

PIB PET and CSF Aβ42 demonstrate a highly significant inverse correlation. Both are presumed to measure brain Aβ amyloid load. Our objectives were to develop a method to transform CSF Aβ42 measures into calculated PIB measures (PIBcalc) of Aβ amyloid load, and to partially validate the method in an independent sample of subjects.

Methods

Forty-one ADNI subjects underwent PIB PET imaging and lumbar puncture (LP) at the same time. This sample, referred to as the “training” sample (9 cognitively normal (CN), 22 MCI, and 10 AD), was used to develop a regression model by which CSF Aβ42 (with APOE ε4 genotype as a covariate) was transformed into units of PIB PET (PIBcalc). An independent “supporting” sample of 362 (105 CN, 164 MCI, 93AD) ADNI subjects who underwent LP but not PIB PET imaging had their CSF Aβ42 values converted to PIBcalc. These values were compared to the overall PIB PET distribution found in the ADNI subjects (n = 102).

Results

A linear regression model demonstrates good prediction of actual PIB PET from CSF Aβ42 measures obtained in the training sample (R2 = 0.77, P<0.001). PIBcalc data (derived from CSF Aβ42) in the supporting sample of 362 ADNI subjects who underwent LP but not PIB PET imaging demonstrates group-wise distributions that are highly consistent with the larger ADNI PIB PET distribution and with published PIB PET imaging studies.

Conclusion

Although the precise parameters of this model are specific for the ADNI sample, we conclude that CSF Aβ42 can be transformed into calculated PIB (PIBcalc) measures of Aβ amyloid load. Brain Aβ amyloid load can be ascertained at baseline in therapeutic or observational studies by either CSF or amyloid PET imaging and the data can be pooled using well-established multiple imputation techniques that account for the uncertainty in a CSF-based calculated PIB value.

A major recent discovery was the identification of an expansion of a non-coding GGGGCC hexanucleotide repeat in the C9ORF72 gene in patients with frontotemporal dementia and amyotrophic lateral sclerosis. Mutations in two other genes are known to account for familial frontotemporal dementia: microtubule-associated protein tau and progranulin. Although imaging features have been previously reported in subjects with mutations in tau and progranulin, no imaging features have been published in C9ORF72. Furthermore, it remains unknown whether there are differences in atrophy patterns across these mutations, and whether regional differences could help differentiate C9ORF72 from the other two mutations at the single-subject level. We aimed to determine the regional pattern of brain atrophy associated with the C9ORF72 gene mutation, and to determine which regions best differentiate C9ORF72 from subjects with mutations in tau and progranulin, and from sporadic frontotemporal dementia. A total of 76 subjects, including 56 with a clinical diagnosis of behavioural variant frontotemporal dementia and a mutation in one of these genes (19 with C9ORF72 mutations, 25 with tau mutations and 12 with progranulin mutations) and 20 sporadic subjects with behavioural variant frontotemporal dementia (including 50% with amyotrophic lateral sclerosis), with magnetic resonance imaging were included in this study. Voxel-based morphometry was used to assess and compare patterns of grey matter atrophy. Atlas-based parcellation was performed utilizing the automated anatomical labelling atlas and Statistical Parametric Mapping software to compute volumes of 37 regions of interest. Hemispheric asymmetry was calculated. Penalized multinomial logistic regression was utilized to create a prediction model to discriminate among groups using regional volumes and asymmetry score. Principal component analysis assessed for variance within groups. C9ORF72 was associated with symmetric atrophy predominantly involving dorsolateral, medial and orbitofrontal lobes, with additional loss in anterior temporal lobes, parietal lobes, occipital lobes and cerebellum. In contrast, striking anteromedial temporal atrophy was associated with tau mutations and temporoparietal atrophy was associated with progranulin mutations. The sporadic group was associated with frontal and anterior temporal atrophy. A conservative penalized multinomial logistic regression model identified 14 variables that could accurately classify subjects, including frontal, temporal, parietal, occipital and cerebellum volume. The principal component analysis revealed similar degrees of heterogeneity within all disease groups. Patterns of atrophy therefore differed across subjects with C9ORF72, tau and progranulin mutations and sporadic frontotemporal dementia. Our analysis suggested that imaging has the potential to be useful to help differentiate C9ORF72 from these other groups at the single-subject level.

Behavioural variant frontotemporal dementia is characterized by a change in comportment. It is associated with considerable functional decline over the course of the illness albeit with sometimes dramatic variability among patients. It is unknown whether any baseline features, or combination of features, could predict rate of functional decline in behavioural variant frontotemporal dementia. The aim of this study was to investigate the effects of different baseline clinical, neuropsychological, neuropsychiatric, genetic and anatomic predictors on the rate of functional decline as measured by the Clinical Dementia Rating Sum of Boxes scale. We identified 86 subjects with behavioural variant frontotemporal dementia that had multiple serial Clinical Dementia Rating Sum of Boxes assessments (mean 4, range 2–18). Atlas-based parcellation was used to generate volumes for specific regions of interest at baseline. Volumes were utilized to classify subjects into different anatomical subtypes using the advanced statistical technique of cluster analysis and were assessed as predictor variables. Composite scores were generated for the neuropsychological domains of executive, language, memory and visuospatial function. Behaviours from the brief questionnaire form of the Neuropsychiatric Inventory were assessed. Linear mixed-effects regression modelling was used to determine which baseline features predict rate of future functional decline. Rates of functional decline differed across the anatomical subtypes of behavioural variant frontotemporal dementia, with faster rates observed in the frontal dominant and frontotemporal subtypes. In addition, subjects with poorer performance on neuropsychological tests of executive, language and visuospatial function, less disinhibition, agitation/aggression and night-time behaviours at presentation, and smaller medial, lateral and orbital frontal lobe volumes showed faster rates of decline. In many instances, the effect of the predictor variables observed across all subjects was also preserved within anatomical subtypes. Furthermore, some of the predictor variables improved our prediction of rate of functional decline after anatomical subtype was taken into account. In particular, age at onset was a highly significant predictor but only after adjusting for subtype. We also found that although some predictor variables, for example gender, Mini-Mental State Examination score, and apathy/indifference, did not affect the rate of functional decline; these variables were associated with the actual Clinical Dementia Rating Sum of Boxes score estimated for any given time-point. These findings suggest that in behavioural variant frontotemporal dementia, rate of functional decline is driven by the combination of anatomical pattern of atrophy, age at onset, and neuropsychiatric characteristics of the subject at baseline.

Objective

When using imaging to predict time to progression from mild cognitive impairment (MCI) to Alzheimer's disease (AD), time-to-event statistical methods account for varying lengths of follow-up times among subjects whereas two-sample t-tests in voxel-based morphometry (VBM) do not. Our objectives were to apply a time-to-event voxel-based analytic method to identify regions on MRI where atrophy is associated with significantly increased risk of future progression to AD in subjects with MCI and to compare it to traditional voxel-level patterns obtained by applying two-sample methods. We also compared the power required to detect an association using time-to-event methods versus two-sample approaches.

Methods

Subjects with MCI at baseline were followed prospectively. The event of interest was clinical diagnosis of AD. Cox proportional hazards models adjusted for age, sex, and education were used to estimate the relative hazard of progression from MCI to AD based on rank-transformed voxel-level gray matter density (GMD) estimates.

Results

The greatest risk of progression to AD was associated with atrophy of the medial temporal lobes. Patients ranked at the 25th percentile of GMD in these regions had more than a doubling of risk of progression to AD at a given time-point compared to patients at the 75th percentile. Power calculations showed the time-to-event approach to be more efficient than the traditional two-sample approach.

Conclusions

We present a new voxel-based analytic method that incorporates time-to-event statistical methods. In the context of a progressive disease like AD, time-to-event VBM seems more appropriate and powerful than traditional two-sample methods.

OBJECTIVE

To investigate the association of type 2 diabetes with subcortical infarctions.

RESEARCH DESIGN AND METHODS

We investigated this association in subjects with type 2 diabetes (case subjects; n = 93) and without type 2 diabetes (control subjects; n = 186), matched by age, sex, and years of education. Participants were a subset of the Mayo Clinic Study of Aging (median age 79 years) who had undergone magnetic resonance imaging.

RESULTS

The frequency of subcortical infarctions was 39% in case subjects and 29% in control subjects (odds ratio 1.59 [95% CI 0.91–2.75]). The association was stronger in case subjects without treatment (2.60 [1.11–6.08]) and in case subjects with diabetes-related complications (1.96 [1.02–3.74]) compared with control subjects.

CONCLUSIONS

These findings suggest that untreated type 2 diabetes and type 2 diabetes with complications are associated with subcortical infarctions.

Quantitative Sudomotor Axon Reflex Testing is a useful measure of post ganglionic sudomotor function. The test is based on the iontophoresis of an acetylcholine solution which induces a local sweat response. We have previously described a gel-based vehicle that may provide another option for the iontophoresis of acetylcholine. It was our objective to compare the influence of the vehicle (gel versus solution) on sudomotor recordings and perceived discomfort. Results show gel-based vehicles are very similar to solution-based vehicles during Quantitative Sudomotor Axon Reflex Testing.

The objective of this study was to investigate how a measure of educational and occupational attainment, a component of cognitive reserve, modifies the relationship between biomarkers of pathology and cognition in Alzheimer's disease. The biomarkers evaluated quantified neurodegeneration via atrophy on magnetic resonance images, neuronal injury via cerebral spinal fluid t-tau, brain amyloid-β load via cerebral spinal fluid amyloid-β1–42 and vascular disease via white matter hyperintensities on T2/proton density magnetic resonance images. We included 109 cognitively normal subjects, 192 amnestic patients with mild cognitive impairment and 98 patients with Alzheimer's disease, from the Alzheimer's Disease Neuroimaging Initiative study, who had undergone baseline lumbar puncture and magnetic resonance imaging. We combined patients with mild cognitive impairment and Alzheimer's disease in a group labelled ‘cognitively impaired’ subjects. Structural Abnormality Index scores, which reflect the degree of Alzheimer's disease-like anatomic features on magnetic resonance images, were computed for each subject. We assessed Alzheimer's Disease Assessment Scale (cognitive behaviour section) and mini-mental state examination scores as measures of general cognition and Auditory–Verbal Learning Test delayed recall, Boston naming and Trails B scores as measures of specific domains in both groups of subjects. The number of errors on the American National Adult Reading Test was used as a measure of environmental enrichment provided by educational and occupational attainment, a component of cognitive reserve. We found that in cognitively normal subjects, none of the biomarkers correlated with the measures of cognition, whereas American National Adult Reading Test scores were significantly correlated with Boston naming and mini-mental state examination results. In cognitively impaired subjects, the American National Adult Reading Test and all biomarkers of neuronal pathology and amyloid load were independently correlated with all cognitive measures. Exceptions to this general conclusion were absence of correlation between cerebral spinal fluid amyloid-β1–42 and Boston naming and Trails B. In contrast, white matter hyperintensities were only correlated with Boston naming and Trails B results in the cognitively impaired. When all subjects were included in a flexible ordinal regression model that allowed for non-linear effects and interactions, we found that the American National Adult Reading Test had an independent additive association such that better performance was associated with better cognitive performance across the biomarker distribution. Our main conclusions included: (i) that in cognitively normal subjects, the variability in cognitive performance is explained partly by the American National Adult Reading Test and not by biomarkers of Alzheimer's disease pathology; (ii) in cognitively impaired subjects, the American National Adult Reading Test, biomarkers of neuronal pathology (structural magnetic resonance imaging and cerebral spinal fluid t-tau) and amyloid load (cerebral spinal fluid amyloid-β1–42) all independently explain variability in general cognitive performance; and (iii) that the association between cognition and the American National Adult Reading Test was found to be additive rather than to interact with biomarkers of Alzheimer's disease pathology.

Q-Sweat, a commercial quantitative sweat measurement system, is modeled on Quantitative Sudomotor Axon Reflex Testing (QSART). The current study investigated the sweat response using Q-Sweat and Mayo-QSART recordings under identical conditions in healthy normal controls. Ninety-four participants were recruited for this study. All participants underwent randomized bilateral QSART recordings over the four standard recording regions. For both men and women, Wilcoxon signed rank tests of paired differences showed significantly lower volumes at each of the four sites for Q-Sweat vs. Mayo-QSART. Linear regression analysis was used to estimate the relationship between Q-Sweat and Mayo-QSART volume measurements separately for men and women. Although there was variability about the regression lines, these fitted models can be used to estimate the expected Mayo-QSART volume given an observed Q-Sweat volume, although it is preferable to use the Q-Sweat normative database directly. We hypothesize that the constant current generator used in conjunction with Q-Sweat provides a less efficient iontophoresis of acetylcholine than the Mayo-constructed constant current stimulator and results in lower volumes.

Objective

To investigate the impact white matter hyperintensities (WMH) detected on MRI have on motor dysfunction and cognitive impairment in non-demented elderly subjects.

Design

Cross-sectional study.

Setting

Population-based study on the incidence and prevalence of cognitive impairment in Olmsted County, MN.

Participants

A total of 148 non-demented elderly (65 males) ranging in age from 73 to 91 years.

Main Outcome Measures

We measured the percentage of the total white matter volume classified as WMH (WMHp) in a priori defined brain regions (i.e. frontal, temporal, parietal, occipital, periventricular or subcortical). Motor impairment was evaluated qualitatively using the Unified Parkinson’s Disease Rating Scale (UPDRS) summary measures of motor skills and quantitatively using a digitized portable walkway system. Four cognitive domains were evaluated using z-scores of memory, language, executive function, and visuospatial reasoning.

Results

A higher WMHp in all regions except occipital was associated with lower executive function z-score (p-value<0.01). A higher WMHp in all regions, but most strongly for parietal lobe, correlated with higher gait/postural-stability/posture UPDRS sum (p-value<0.01). A higher WMHp whether periventricular, subcortical or lobar correlated with reduced velocity (p-value<0.001).

Conclusions

We conclude that executive function is the primary cognitive domain affected by WMH burden. The data suggests that WMH in the parietal lobe are chiefly responsible for reduced balance and postural support compared to the other three lobes and may alter integration of sensory information via parietal lobe dysfunction in the aging brain. It is of interest that parietal WM changes were not the predominant correlate with motor speed, lending evidence to a global involvement of neural networks in gait velocity.

The behavioural variant of frontotemporal dementia is a progressive neurodegenerative syndrome characterized by changes in personality and behaviour. It is typically associated with frontal lobe atrophy, although patterns of atrophy are heterogeneous. The objective of this study was to examine case-by-case variability in patterns of grey matter atrophy in subjects with the behavioural variant of frontotemporal dementia and to investigate whether behavioural variant of frontotemporal dementia can be divided into distinct anatomical subtypes. Sixty-six subjects that fulfilled clinical criteria for a diagnosis of the behavioural variant of frontotemporal dementia with a volumetric magnetic resonance imaging scan were identified. Grey matter volumes were obtained for 26 regions of interest, covering frontal, temporal and parietal lobes, striatum, insula and supplemental motor area, using the automated anatomical labelling atlas. Regional volumes were divided by total grey matter volume. A hierarchical agglomerative cluster analysis using Ward's clustering linkage method was performed to cluster the behavioural variant of frontotemporal dementia subjects into different anatomical clusters. Voxel-based morphometry was used to assess patterns of grey matter loss in each identified cluster of subjects compared to an age and gender-matched control group at P < 0.05 (family-wise error corrected). We identified four potentially useful clusters with distinct patterns of grey matter loss, which we posit represent anatomical subtypes of the behavioural variant of frontotemporal dementia. Two of these subtypes were associated with temporal lobe volume loss, with one subtype showing loss restricted to temporal lobe regions (temporal-dominant subtype) and the other showing grey matter loss in the temporal lobes as well as frontal and parietal lobes (temporofrontoparietal subtype). Another two subtypes were characterized by a large amount of frontal lobe volume loss, with one subtype showing grey matter loss in the frontal lobes as well as loss of the temporal lobes (frontotemporal subtype) and the other subtype showing loss relatively restricted to the frontal lobes (frontal-dominant subtype). These four subtypes differed on clinical measures of executive function, episodic memory and confrontation naming. There were also associations between the four subtypes and genetic or pathological diagnoses which were obtained in 48% of the cohort. The clusters did not differ in behavioural severity as measured by the Neuropsychiatric Inventory; supporting the original classification of the behavioural variant of frontotemporal dementia in these subjects. Our findings suggest behavioural variant of frontotemporal dementia can therefore be subdivided into four different anatomical subtypes.

Biomarkers of brain Aβ amyloid deposition can be measured either by cerebrospinal fluid Aβ42 or Pittsburgh compound B positron emission tomography imaging. Our objective was to evaluate the ability of Aβ load and neurodegenerative atrophy on magnetic resonance imaging to predict shorter time-to-progression from mild cognitive impairment to Alzheimer’s dementia and to characterize the effect of these biomarkers on the risk of progression as they become increasingly abnormal. A total of 218 subjects with mild cognitive impairment were identified from the Alzheimer’s Disease Neuroimaging Initiative. The primary outcome was time-to-progression to Alzheimer’s dementia. Hippocampal volumes were measured and adjusted for intracranial volume. We used a new method of pooling cerebrospinal fluid Aβ42 and Pittsburgh compound B positron emission tomography measures to produce equivalent measures of brain Aβ load from either source and analysed the results using multiple imputation methods. We performed our analyses in two phases. First, we grouped our subjects into those who were ‘amyloid positive’ (n = 165, with the assumption that Alzheimer's pathology is dominant in this group) and those who were ‘amyloid negative’ (n = 53). In the second phase, we included all 218 subjects with mild cognitive impairment to evaluate the biomarkers in a sample that we assumed to contain a full spectrum of expected pathologies. In a Kaplan–Meier analysis, amyloid positive subjects with mild cognitive impairment were much more likely to progress to dementia within 2 years than amyloid negative subjects with mild cognitive impairment (50 versus 19%). Among amyloid positive subjects with mild cognitive impairment only, hippocampal atrophy predicted shorter time-to-progression (P < 0.001) while Aβ load did not (P = 0.44). In contrast, when all 218 subjects with mild cognitive impairment were combined (amyloid positive and negative), hippocampal atrophy and Aβ load predicted shorter time-to-progression with comparable power (hazard ratio for an inter-quartile difference of 2.6 for both); however, the risk profile was linear throughout the range of hippocampal atrophy values but reached a ceiling at higher values of brain Aβ load. Our results are consistent with a model of Alzheimer’s disease in which Aβ deposition initiates the pathological cascade but is not the direct cause of cognitive impairment as evidenced by the fact that Aβ load severity is decoupled from risk of progression at high levels. In contrast, hippocampal atrophy indicates how far along the neurodegenerative path one is, and hence how close to progressing to dementia. Possible explanations for our finding that many subjects with mild cognitive impairment have intermediate levels of Aβ load include: (i) individual subjects may reach an Aβ load plateau at varying absolute levels; (ii) some subjects may be more biologically susceptible to Aβ than others; and (iii) subjects with mild cognitive impairment with intermediate levels of Aβ may represent individuals with Alzheimer’s disease co-existent with other pathologies.

Background and Purpose

Decreased glucose metabolism in the temporal and parietal lobes on [18F]fluorodeoxyglucose (FDG) PET is recognized as an early imaging marker for the Alzheimer’s disease (AD) pathology. Our objective was to investigate the effects of age on FDG PET findings in aMCI.

Methods

25 patients with aMCI at 55–86 years of age (median = 73), and 25 age and gender matched cognitively normal (CN) subjects underwent FDG PET. SPM5 was used to compare the FDG uptake in aMCI-old (>73 years) and aMCI-young (>73 years) patients to CN subjects. The findings in the aMCI-old patients were independently validated in a separate cohort of 10 aMCI and 13 CN subjects older than 73 years of age.

Results

The pattern of decreased glucose metabolism and gray matter atrophy in the medial temporal, posterior cingulate, precuneus, lateral parietal and temporal lobes in aMCI-young subjects was consistent with the typical pattern observed in AD. The pattern of glucose metabolic changes in aMCI-old subjects was different, predominantly involving the frontal lobes and the left parietal lobe. Gray matter atrophy in aMCI-old subjects was less pronounced than the aMCI-young subjects involving the hippocampus and the basal forebrain in both hemispheres

Conclusion

Pathological heterogeneity may be underlying the absence of AD-like glucose metabolic changes in older compared to younger aMCI patients. This may be an important consideration for the clinical use of temporoparietal hypometabolism on FDG PET as a marker for early diagnosis of AD in aMCI.

Objective

To study the effect of apolipoprotein E ε4 status on biomarkers of neurodegeneration (atrophy on magnetic resonance imaging [MRI]), neuronal injury (cerebrospinal fluid [CSF] t-tau), and brain Aβ amyloid load (CSF Aβ1–42) in cognitively normal subjects (CN), amnestic subjects with mild cognitive impairment (aMCI), and patients with Alzheimer disease (AD).

Methods

We included all 399 subjects (109 CN, 192 aMCI, 98 AD) from the Alzheimer's Disease Neuroimaging Initiative study with baseline CSF and MRI scans. Structural Abnormality Index (STAND) scores, which reflect the degree of AD-like anatomic features on MRI, were computed for each subject.

Results

A clear ε4 allele dose effect was seen on CSF Aβ1–42 levels within each clinical group. In addition, the proportion of the variability in Aβ1–42 levels explained by APOE ε4 dose was significantly greater than the proportion of the variability explained by clinical diagnosis. On the other hand, the proportion of the variability in CSF t-tau and MRI atrophy explained by clinical diagnosis was greater than the proportion of the variability explained by APOE ε4 dose; however, this effect was only significant for STAND scores.

Interpretation

Low CSF Aβ1–42 (surrogate for Aβ amyloid load) is more closely linked to the presence of APOE ε4 than to clinical status. In contrast, MRI atrophy (surrogate for neurodegeneration) is closely linked with cognitive impairment, whereas its association with APOE ε4 is weaker. The data in this paper support a model of AD in which CSF Aβ1–42 is the earliest of the 3 biomarkers examined to become abnormal in both APOE carriers and noncarriers.

This study describes a novel gel based vehicle for the delivery of acetylcholine (ACh) during quantitative sudomotor axon reflex testing (QSART). A dose and current response study were undertaken on 20 healthy control participants to characterize the efficiency of a gel based vehicle for the delivery of ACh. Values obtained for total sweat volume and latency to sweat onset with gel iontophoresis of ACh during QSART were comparable to previously published normative data using solution based vehicles. Patient discomfort, utilizing the gel based vehicle during the QSART procedure, was minimal. Improvement in iontophoresis using the gel formulation as a vehicle for ACh delivery has the potential to lower the voltage required to overcome skin resistance during QSART and may result in improved patient comfort during the procedure.

Objective

The severity, distribution, and pattern of autonomic failure appear to be different in multiple system atrophy (MSA) compared with Parkinson’s disease (PD), but reports have been retrospective reviews and have tended to exclude PD with autonomic failure (PD_AF). We report preliminary results of a prospective ongoing study of MSA and PD, with a large subset of PD_AF (25%) to evaluate autonomic indices that distinguish MSA from PD.

Methods

We used Consensus criteria, detailed autonomic studies (composite autonomic symptom score (COMPASS), composite autonomic severity score (CASS), thermoregulatory sweat test percent anhidrosis (TST%), plasma catecholamines, and functional scales (Unified MSA rating scale (UMSARS) I–IV, Hoehn-Yahr grading) on a prospective, repeated, and ongoing basis.

Results

We report the results of a study based on 52 patients with MSA (61.1±7.8 years; BMI 27.2±4.6; Hoehn-Yahr grade, 3.2±0.9; UMSARS_1 21.5±7.4; UMSARS_2, 22.7±9.0) and 29 patients with PD, including PD_AF (66.0±8.1 years; BMI 26.6±.5.5; Hoehn-Yahr grade, 2.2±0.8; UMSARS_1 10.4±6.1; UMSARS_2, 13.0±5.9). Autonomic indices were highly significantly more abnormal in MSA than PD (P<0.001) for each of: CASS (5.9±1.9 vs. 3.3±2.3), COMPASS (54.4±21.8 vs. 24.7±20.5), TST% (57.4±35.2 vs. 9.9±17.7). These differences were sustained and greater at 1 year follow-up indicating a greater rate of progression of dysautonomia in MSA than PD.

Interpretation

The severity, distribution, and pattern of autonomic deficits at entry will distinguish MSA from PD and MSA from PD_AF. These differences continue and increase with follow-up. Our ongoing conclusion is that autonomic function tests can separate MSA from PD. Autonomic indices support the notion that the primary lesion in PD is ganglionic/postganglionic while MSA is preganglionic.

This study tests if measures of hippocampal water diffusivity at baseline can predict future progression to Alzheimer’s Disease (AD) in amnestic mild cognitive impairment (aMCI). Higher baseline hippocampal diffusivity was associated with a greater hazard of progression to AD in aMCI (p=0.002). MR diffusion weighted imaging (DWI) may help identify patients with aMCI who will progress to AD as well or better than structural MRI measures of hippocampal atrophy.

Objective

To determine the 1H MR spectroscopic (MRS) findings and inter-group differences among common dementias: Alzheimer's disease (AD), vascular dementia (VaD), dementia with Lewy bodies (DLB), and frontotemporal lobar degeneration (FTLD).

Methods

We consecutively recruited 206 normal elderly, 121 patients with AD, 41 with FTLD, 20 with DLB, and 8 with VaD. We evaluated the 1H MRS metabolite ratio changes in common dementias with respect to normal, and also differences among the common dementias.

Results

N-acetylaspartate/Creatine (NAA/Cr) was lower than normal in patients with AD, FTLD, and VaD. Myo-inositol (mI)/Cr was higher than normal in patients with AD and FTLD. Choline (Cho)/Cr was higher than normal in patients with, AD, FTLD, and DLB. There were no metabolite differences between patients with AD and FTLD, nor between patients with DLB and VaD. NAA /Cr was lower in patients with AD and FTLD than DLB. MI /Cr was higher in patients with AD and FTLD than VaD. MI /Cr was also higher in patients with FTLD than DLB.

Conclusions

NAA/Cr levels are decreased in dementias that are characterized by neuron loss such as AD, FTLD, and VaD. MI/Cr levels are elevated in dementias that are pathologically characterized by gliosis such as AD and FTLD. Cho/Cr levels are elevated in dementias that are characterized by a profound cholinergic deficit such as AD and DLB.

Magnetic Resonance (MR)- based volume measurements of atrophy are potential markers of disease progression in patients with amnestic mild cognitive impairment (aMCI) and Alzheimer’s disease (AD). Longitudinal changes in 1H MR spectroscopy (1H MRS) metabolite markers have not been characterized in aMCI subjects. Our objective was to determine the longitudinal 1H MRS metabolite changes in patients with aMCI, and AD, and to compare 1H MRS metabolite ratios and ventricular volumes in tracking clinical disease progression in AD. The neuronal integrity marker N-acetylaspartate/Creatine ratio declined in aMCI and AD patients compared to cognitively normal elderly. The changein 1H MRS metabolite ratios correlated with clinical progression about as strongly as the rate of ventricular expansion, suggesting that 1H MRS metabolite ratios may be useful markers for the progression of AD. Choline/Creatine ratio declined in stable aMCI, compared to converter aMCI patients and cognitively normal elderly, which may be related to a compensatory mechanism in aMCI patients who did not to progress to AD.

Functional MRI (fMRI) shows changes in multiple regions in amnestic MCI (aMCI). The concept of MCI recently evolved to include non-amnestic syndromes so little is known about fMRI changes in these individuals. This study investigated activation during visual complex scene encoding and recognition in 29 cognitively normal (CN) elderly, 19 individuals with aMCI and 12 individuals with non-amnestic MCI (naMCI). During encoding CN activated an extensive network that included bilateral occipital-parietal-temporal cortex, precuneus, posterior cingulate, thalamus, insula, and medial, anterior, and lateral frontal regions. Amnestic MCI activated an anatomic subset of these regions. Non-amnestic MCI activated an even smaller anatomic subset. During recognition, CN activated the same regions observed during encoding except the precuneus. Both MCI groups again activated a subset of the regions activated by CN. During encoding, CN had greater activation than aMCI and naMCI in bilateral temporo-parietal and frontal regions. During recognition, CN had greater activation than aMCI in predominantly temporo-parietal regions bilaterally while CN had greater activation than naMCI in larger areas involving bilateral temporo-parietal and frontal regions. The diminished parietal and frontal activation in naMCI may reflect compromised ability to perform non-memory (i.e., attention/executive, visuospatial function) components of the task.