To characterize the shape of the trajectories of Alzheimer’s Disease (AD) biomarkers as a function of MMSE.
Longitudinal registries from the Mayo Clinic and the Alzheimer’s Disease Neuroimaging Initiative (ADNI).
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).
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.
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.
Alzheimer’s disease biomarkers; Magnetic Resonance Imaging; cerebro spinal fluid; amyloid PET imaging; FDG PET imaging
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.
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.
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.
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.
REM sleep behavior disorder (RBD) is associated with neurodegenerative disease and particularly with the synucleinopathies. Convenience samples involving subjects with idiopathic RBD have suggested an increased risk of incident mild cognitive impairment (MCI), dementia (usually dementia with Lewy bodies) or Parkinson’s disease (PD). There is no data on such risk in a population-based sample.
Cognitively normal subjects aged 70–89 in a population-based study of aging who screened positive for probable RBD using the Mayo Sleep Questionnaire were followed at 15 month intervals. In a Cox Proportional Hazards Model, we measured the risk of developing MCI, dementia, PD among the exposed (pRBD+) and unexposed (pRBD−) cohorts.
Forty-four subjects with pRBD+ at enrollment (median duration of pRBD features was 7.5 years), and 607 pRBD− subjects, were followed prospectively for a median of 3.8 years. Fourteen of the pRBD+ subjects developed MCI and one developed PD (15/44=34% developed MCI / PD); none developed dementia. After adjustment for age, sex, education, and medical comorbidity, pRBD+ subjects were at increased risk of MCI / PD [Hazard Ratio (HR) 2.2, 95% Confidence Interval (95%CI) 1.3 – 3.9; p=0.005]. Inclusion of subjects who withdrew from the study produced similar results, as did exclusion of subjects with medication-associated RBD. Duration of pRBD symptoms did not predict the development of MCI / PD (HR 1.05 per 10 years, 95%CI 0.84 – 1.3; p=0.68).
In this population-based cohort study, we observed that pRBD confers a 2.2-fold increased risk of developing MCI / PD over four years.
sleep disorders; parasomnias; dementia; Alzheimer’s disease; dementia with Lewy bodies; parkinsonism; synuclein
To examine the association between computer use, physical exercise, aging, and mild cognitive impairment (MCI).
Patients and Methods
The Mayo Clinic Study of Aging is a population-based study of aging and MCI in Olmsted County, Minnesota. The study sample consists of a random sample of 926 nondemented individuals aged 70 to 93 years who completed self-reported questionnaires on physical exercise, computer use, and caloric intake within 1 year of the date of interview. The study was conducted from April 1, 2006, through November 30, 2008. An expert consensus panel classified each study participant as cognitively normal or having MCI on the basis of published criteria.
Using a multivariable logistic regression model, we examined the impact of the presence during the study period of 2 lifestyle factors (physical exercise and computer use) after adjusting for a third lifestyle factor (caloric intake) on aging and MCI. We also adjusted for age, sex, education, medical comorbidity, and depression. The median daily caloric intake was significantly higher in participants with MCI than in controls (odds ratio, 1.04; 95% confidence interval, 1.02-1.06; P=.001). Participants who engaged in both moderate physical exercise and computer use had significantly decreased odds of having MCI (odds ratio [95% confidence interval], 0.36 [0.20-0.68]) compared with the reference group. In the interaction analyses, there was an additive interaction (P=.012) but not multiplicative interaction (P=.780).
In this population-based sample, the presence of both physical exercise and computer use as assessed via survey was associated with decreased odds of having MCI, after adjustment for caloric intake and traditional confounders.
CDR, Clinical Dementia Rating; CI, confidence interval; MCI, mild cognitive impairment; OR, odds ratio
Alzheimer's disease (AD) can present with non-amnestic clinical syndromes. We investigated whether there is an imaging signature of AD pathology in these atypical subjects. We identified 14 subjects that had pathological AD, a non-amnestic presentation (i.e. atypical AD), and MRI. These subjects were matched to 14 with clinical and pathological AD (i.e. typical AD), 14 with the same non-amnestic presentations with frontotemporal lobar degeneration (FTLD) pathology, and 20 controls. Voxel-based morphometry and region-of-interest (ROI) analysis were used to assess patterns of grey matter loss. Loss was observed in the temporoparietal cortex in both typical and atypical AD, and showed significantly greater loss than FTLD. However, the medial temporal lobes were more severely affected in typical AD and FTLD compared to atypical AD. A ratio of hippocampal and temporoparietal volumes provided excellent discrimination of atypical AD from FTLD subjects. Temporoparietal atrophy may therefore provide a useful marker of the presence of AD pathology even in subjects with atypical clinical presentations, especially in the context of relative sparing of the hippocampus.
Alzheimer's disease; pathology; voxel-based morphometry; atypical presentation; frontotemporal lobar degeneration; temporoparietal cortex; hippocampus
Expanded glutamine repeats of the ataxin-2 (ATXN2) protein cause spinocerebellar ataxia type 2 (SCA2), a rare neurodegenerative disorder. More recent studies have suggested that expanded ATXN2 repeats are a genetic risk factor for amyotrophic lateral sclerosis (ALS) via an RNA-dependent interaction with TDP-43. Given the phenotypic diversity observed in SCA2 patients, we set out to determine the polymorphic nature of the ATXN2 repeat length across a spectrum of neurodegenerative disorders. In this study, we genotyped the ATXN2 repeat in 3919 neurodegenerative disease patients and 4877 healthy controls and performed logistic regression analysis to determine the association of repeat length with the risk of disease. We confirmed the presence of a significantly higher number of expanded ATXN2 repeat carriers in ALS patients compared with healthy controls (OR = 5.57; P= 0.001; repeat length >30 units). Furthermore, we observed significant association of expanded ATXN2 repeats with the development of progressive supranuclear palsy (OR = 5.83; P= 0.004; repeat length >30 units). Although expanded repeat carriers were also identified in frontotemporal lobar degeneration, Alzheimer's and Parkinson's disease patients, these were not significantly more frequent than in controls. Of note, our study identified a number of healthy control individuals who harbor expanded repeat alleles (31–33 units), which suggests caution should be taken when attributing specific disease phenotypes to these repeat lengths. In conclusion, our findings confirm the role of ATXN2 as an important risk factor for ALS and support the hypothesis that expanded ATXN2 repeats may predispose to other neurodegenerative diseases, including progressive supranuclear palsy.
Hereditary diffuse leukoencephalopathy with spheroids (HDLS) is an autosomal dominantly inherited central nervous system white matter disease with variable clinical presentations including personality and behavioral changes, dementia, depression, parkinsonism, seizures, and others1,2. We combined genome-wide linkage analysis with exome sequencing and identified 14 different mutations affecting the tyrosine kinase domain of the colony stimulating factor receptor 1 (encoded by CSF1R) in 14 families affected by HDLS. In one kindred, the de novo occurrence of the mutation was confirmed. Follow-up sequencing analyses identified an additional CSF1R mutation in a patient clinically diagnosed with corticobasal syndrome (CBS). In vitro, CSF-1 stimulation resulted in the rapid autophosphorylation of selected tyrosine-residues in the kinase domain of wild-type but not mutant CSF1R, suggesting that HDLS may result from a partial loss of CSF1R function. Since CSF1R is a critical mediator of microglial proliferation and differentiation in the brain, our findings suggest an important role for microglial dysfunction in HDLS pathogenesis.
TAR DNA binding protein-43 (TDP-43) immunoreactive neuronal inclusions are detected in 20–30% of Alzheimer disease (AD) brains, but the distribution of this pathology has not been rigorously studied. In this report we describe region-specific distribution and density of TDP-43 positive neuronal cytoplasmic inclusions (NCIs) in clinically demented individuals with high probability AD pathology, all with Braak neurofibrillary tangle stages of V or VI. Sections of hippocampus, amygdala, as well as temporal, frontal and parietal neocortex were analyzed with TDP-43 immunohistochemistry, and the density of NCIs was assessed using a semiquantitative scoring method. Of the 29 cases, 6 had TDP-43 positive NCIs in the amygdala only, and 7 had TDP-43 inclusions restricted to amygdala and hippocampus. In 16 cases TDP-43 immunoreactivity was more widespread, affecting temporal, frontal or parietal neocortex. These findings indicate that medial temporal lobe limbic structures are vulnerable to TDP-43 pathology in advanced AD, and that the amygdala appears to be the most vulnerable region. The distribution of the lesions in this cross-sectional analysis may suggest a progression of TDP-43 pathology in AD, with limbic structures in the medial temporal lobe affected first followed by higher order association cortices.
Amygdala; FTLD-U; FTLD-MND; frontotemporal dementia; motor neuron disease
Pathology underlying behavioral variant frontotemporal dementia (bvFTD) is heterogeneous, with the most common pathologies being Pick’s disease (PiD), corticobasal degeneration (CBD), and FTLD-TDP type 1. Clinical features are unhelpful in differentiating these pathologies. We aimed to determine whether imaging atrophy patterns differ across these pathologies in bvFTD subjects. We identified 15 bvFTD subjects that had volumetric MRI during life and autopsy: five with PiD, five CBD and five FTLD-TDP type 1. Voxel-based morphometry was used to assess atrophy patterns in each bvFTD group compared to 20 age and gender-matched controls. All three pathological groups showed grey matter loss in frontal lobes, although specific patterns of atrophy differed across groups: PiD showed widespread loss in frontal lobes with additional involvement of anterior temporal lobes; CBD showed subtle patterns of loss involving posterior lateral and medial superior frontal lobe; FTLD-TDP type 1 showed widespread loss in frontal, temporal and parietal lobes. Greater parietal loss was observed in FTLD-TDP type 1 compared to both other groups, and greater anterior temporal and medial frontal loss was observed in PiD compared to CBD. Imaging patterns of atrophy in bvFTD vary according to pathological diagnosis and may therefore be helpful in predicting these pathologies in bvFTD.
Frontotemporal dementia; behavioral variant; Pick’s disease; corticobasal degeneration; TDP-43; atrophy; voxel-based morphometry; MRI
Task-free functional magnetic resonance imaging (TF-fMRI) has great potential for advancing the understanding and treatment of neurologic illness. However, as with all measures of neural activity, variability is a hallmark of intrinsic connectivity networks (ICNs) identified by TF-fMRI. This variability has hampered efforts to define a robust metric of connectivity suitable as a biomarker for neurologic illness. We hypothesized that some of this variability rather than representing noise in the measurement process, is related to a fundamental feature of connectivity within ICNs, which is their non-stationary nature. To test this hypothesis, we used a large (n = 892) population-based sample of older subjects to construct a well characterized atlas of 68 functional regions, which were categorized based on independent component analysis network of origin, anatomical locations, and a functional meta-analysis. These regions were then used to construct dynamic graphical representations of brain connectivity within a sliding time window for each subject. This allowed us to demonstrate the non-stationary nature of the brain’s modular organization and assign each region to a “meta-modular” group. Using this grouping, we then compared dwell time in strong sub-network configurations of the default mode network (DMN) between 28 subjects with Alzheimer’s dementia and 56 cognitively normal elderly subjects matched 1∶2 on age, gender, and education. We found that differences in connectivity we and others have previously observed in Alzheimer’s disease can be explained by differences in dwell time in DMN sub-network configurations, rather than steady state connectivity magnitude. DMN dwell time in specific modular configurations may also underlie the TF-fMRI findings that have been described in mild cognitive impairment and cognitively normal subjects who are at risk for Alzheimer’s dementia.
To validate a questionnaire focused on REM sleep behavior disorder (RBD) among participants in an aging and dementia cohort.
RBD is a parasomnia that can develop in otherwise neurologically-normal adults as well as in those with a neurodegenerative disease. Confirmation of RBD requires polysomnography (PSG). A simple screening measure for RBD would be desirable for clinical and research purposes.
We had previously developed the Mayo Sleep Questionnaire (MSQ), a 16 item measure, to screen for the presence of RBD and other sleep disorders. We assessed the validity of the MSQ by comparing the responses of patients’ bed partners with the findings on PSG. All subjects recruited in the Mayo Alzheimer’s Disease Research Center at Mayo Clinic Rochester and Mayo Clinic Jacksonville from 1/00 to 7/08 who had also undergone a PSG were the focus of this analysis.
The study sample was comprised of 176 subjects [150 male; median age 71 years (range 39–90)], with the following clinical diagnoses: normal (n=8), mild cognitive impairment (n=44), Alzheimer’s disease (n=23), dementia with Lewy bodies (n=74), as well as other dementia and/or parkinsonian syndromes (n=27). The core question on recurrent dream enactment behavior yielded a sensitivity (SN) of 98% and specificity (SP) of 74% for the diagnosis of RBD. The profile of responses on four additional subquestions on RBD and one on obstructive sleep apnea improved specificity.
These data suggest that among aged subjects with cognitive impairment and/or parkinsonism, the MSQ has adequate SN and SP for the diagnosis of RBD. The utility of this scale in other patient populations will require further study.
sleep disorders; parasomnias; dementia; Alzheimer’s disease; dementia with Lewy bodies; parkinsonism
We investigated whether engaging in cognitive activities is associated with mild cognitive impairment (MCI) in a cross-sectional study derived from an ongoing population-based study of normal cognitive aging and MCI in Olmsted County, Minnesota. A random sample of 1321 non-demented study participants ages 70 to 89 (n = 1124 cognitively normal persons and n = 197 subjects with MCI) was interviewed about the frequency of cognitive activities carried out in late life (within one year of the date of interview). Computer activities [OR (95% CI) = 0.50 (0.36, 0.71); p < .0001)], craft activities such as knitting, quilting, etc. [0.66 (0.47, 0.93); p = 0.019)], playing games [0.65 (0.47, 0.90); p = 0.010)], and reading books [0.67 (0.49, 0.94); p = 0.019)] were associated with decreased odds of having MCI. Social activities such as traveling were marginally significant [0.71 (0.51, 1.00); p = 0.050)]. Even though the point estimates for reading magazines, playing music, artistic activities, and group activities were associated with reduced odds of having MCI, none reached statistical significance. We could not expect to observe any difference between the two groups on the variable of reading newspapers since almost identical proportions of the two groups (97.4% of normals and 97.5% of the MCI group) were engaged in reading newspapers on a regular basis.
cognitive activities; aging; mild cognitive impairment
Few studies have reported neuropsychiatric symptoms (NPS) in Primary Progressive Aphasia (PPA), a neurodegenerative disorder that primarily affects the left hemisphere. Depression is associated with left-sided stroke, but it remains unclear if depression and other NPS are also associated with PPA. The authors compared the frequency of NPS in 55 cases of PPA with 110 cognitively normal persons matched for age, sex and education. Depression, apathy, agitation, anxiety, appetite change, and irritability are associated with PPA. Hallucinations, delusion and night time behavior were not associated with PPA.
The common neurodegenerative pathologies underlying dementia are Alzheimer’s disease (AD), Lewy body disease (LBD) and Frontotemporal lobar degeneration (FTLD). Our aim was to identify patterns of atrophy unique to each of these diseases using antemortem structural-MRI scans of pathologically-confirmed dementia cases and build an MRI-based differential diagnosis system. Our approach of creating atrophy maps using structural-MRI and applying them for classification of new incoming patients is labeled Differential-STAND (Differential-diagnosis based on STructural Abnormality in NeuroDegeneration). Pathologically-confirmed subjects with a single dementing pathologic diagnosis who had an MRI at the time of clinical diagnosis of dementia were identified: 48 AD, 20 LBD, 47 FTLD-TDP (pathology-confirmed FTLD with TDP-43). Gray matter density in 91 regions-of-interest was measured in each subject and adjusted for head-size and age using a database of 120 cognitively normal elderly. The atrophy patterns in each dementia type when compared to pathologically-confirmed controls mirrored known disease-specific anatomic patterns: AD-temporoparietal association cortices and medial temporal lobe; FTLD-TDP-frontal and temporal lobes and LBD-bilateral amygdalae, dorsal midbrain and inferior temporal lobes. Differential-STAND based classification of each case was done based on a mixture model generated using bisecting k-means clustering of the information from the MRI scans. Leave-one-out classification showed reasonable performance compared to the autopsy gold-standard and clinical diagnosis: AD (sensitivity:90.7%; specificity:84 %), LBD (sensitivity:78.6%; specificity:98.8%) and FTLD-TDP (sensitivity:84.4%; specificity:93.8%). The proposed approach establishes a direct a priori relationship between specific topographic patterns on MRI and “gold standard” of pathology which can then be used to predict underlying dementia pathology in new incoming patients.
MRI; Alzheimer’s disease; Lewy body disease; Frontotemporal lobar degeneration
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.
frontotemporal dementia; magnetic resonance imaging; C9ORF72; tau; progranulin
Numerous kindreds with familial frontotemporal dementia and/or amyotrophic lateral sclerosis have been linked to chromosome 9, and an expansion of the GGGGCC hexanucleotide repeat in the non-coding region of chromosome 9 open reading frame 72 has recently been identified as the pathogenic mechanism. We describe the key characteristics in the probands and their affected relatives who have been evaluated at Mayo Clinic Rochester or Mayo Clinic Florida in whom the hexanucleotide repeat expansion were found. Forty-three probands and 10 of their affected relatives with DNA available (total 53 subjects) were shown to carry the hexanucleotide repeat expansion. Thirty-six (84%) of the 43 probands had a familial disorder, whereas seven (16%) appeared to be sporadic. Among examined subjects from the 43 families (n = 63), the age of onset ranged from 33 to 72 years (median 52 years) and survival ranged from 1 to 17 years, with the age of onset <40 years in six (10%) and >60 in 19 (30%). Clinical diagnoses among examined subjects included behavioural variant frontotemporal dementia with or without parkinsonism (n = 30), amyotrophic lateral sclerosis (n = 18), frontotemporal dementia/amyotrophic lateral sclerosis with or without parkinsonism (n = 12), and other various syndromes (n = 3). Parkinsonism was present in 35% of examined subjects, all of whom had behavioural variant frontotemporal dementia or frontotemporal dementia/amyotrophic lateral sclerosis as the dominant clinical phenotype. No subject with a diagnosis of primary progressive aphasia was identified with this mutation. Incomplete penetrance was suggested in two kindreds, and the youngest generation had significantly earlier age of onset (>10 years) compared with the next oldest generation in 11 kindreds. Neuropsychological testing showed a profile of slowed processing speed, complex attention/executive dysfunction, and impairment in rapid word retrieval. Neuroimaging studies showed bilateral frontal abnormalities most consistently, with more variable degrees of parietal with or without temporal changes; no case had strikingly focal or asymmetric findings. Neuropathological examination of 14 patients revealed a range of transactive response DNA binding protein molecular weight 43 pathology (10 type A and four type B), as well as ubiquitin-positive cerebellar granular neuron inclusions in all but one case. Motor neuron degeneration was detected in nine patients, including five patients without ante-mortem signs of motor neuron disease. While variability exists, most cases with this mutation have a characteristic spectrum of demographic, clinical, neuropsychological, neuroimaging and especially neuropathological findings.
frontotemporal dementia; amyotrophic lateral sclerosis; motor neuron disease; TDP-43; neurogenetics; chromosome 9
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.
frontotemporal dementia; behaviour; functional decline; brain volumes; mixed effects models
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.
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.
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.
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.
Alzheimer Disease; mild cognitive impairment; magnetic resonance imaging; Cox proportional hazards model
Mutations in progranulin (PGRN) are associated with frontotemporal dementia with or without parkinsonism. We describe the prominent phenotypic variability within and among eight kindreds evaluated at Mayo Clinic Rochester and/or Mayo Clinic Jacksonville in whom mutations in PGRN were found. All available clinical, genetic, neuroimaging and neuropathologic data was reviewed. Age of onset ranged from 49 to 88 years and disease duration ranged from 1 to 14 years. Clinical diagnoses included frontotemporal dementia (FTD), primary progressive aphasia, FTD with parkinsonism, parkinsonism, corticobasal syndrome, Alzheimer’s disease, amnestic mild cognitive impairment, and others. One kindred exhibited maximal right cerebral hemispheric atrophy in all four affected individuals, while another had maximal left hemisphere involvement in all three of the affected. Neuropathologic examination of 13 subjects revealed frontotemporal lobar degeneration with ubiquitin-positive inclusions plus neuronal intranuclear inclusions in all cases. Age of onset, clinical phenotypes and MRI findings associated with most PGRN mutations varied significantly both within and among kindreds. Some kindreds with PGRN mutations exhibited lateralized topography of degeneration across all affected individuals.
Frontotemporal dementia; FTDP-17; Progranulin; PGRN; MRI
We compare patterns of grey matter loss on MRI in subjects presenting as corticobasal syndrome (CBS) with Alzheimer disease pathology (CBS-AD) to those presenting as CBS with corticobasal degeneration pathology (CBS-CBD). Voxel-based morphometry was used to compare patterns of grey matter loss in pathologically confirmed CBS-AD subjects (n=5) and CBS-CBD subjects (n=6) to a group of normal controls (n=20), and to each other. Atlas based parcellation using the automated anatomic labeling atlas was also utilized in a region-of-interest analysis to account for laterality. The CBS-AD subjects were younger at the time of scan compared to CBS-CBD subjects (median: 60 years vs 69; P=0.04). After adjusting for age at time of MRI scan, the CBS-AD subjects showed loss in posterior frontal, temporal, and superior and inferior parietal lobes, while CBS-CBD showed more focal loss predominantly in the posterior frontal lobes, compared to controls. In both CBS-AD and CBS-CBD groups there was basal ganglia volume loss, yet relative sparing of hippocampi. On direct comparisons between the two subject groups, CBS-AD showed greater loss in both temporal and inferior parietal cortices than CBS-CBD. No regions showed greater loss in the CBS-CBD group compared to the CBS-AD group. These findings persisted when laterality was taken into account. In subjects presenting with CBS, prominent temporoparietal, especially posterior temporal and inferior parietal, atrophy may be a clue to the presence of underlying AD pathology.
Voxel based morphometry; Alzheimer’s disease; Corticobasal syndrome; Corticobasal degeneration; Region-of-Interest
Background and Purpose
Frontotemporal lobar degeneration (FTLD) can be subdivided into those in which the abnormal protein is tau (FTLD-TAU), the TAR DNA binding protein 43 (FTLD-TDP) and the fused in sarcoma protein (FTLD-FUS). We have observed severe caudate atrophy at autopsy in FTLD-FUS, and hence we aimed to determine whether caudate atrophy on MRI is a feature that can distinguish FTLD-FUS from FTLD-TDP and FTLD-TAU.
From a cohort of 207 cases of FTLD we identified all cases of FTLD-FUS that had a volumetric antemortem head MRI (n=3). Caudate and frontal lobe volumes were measured in all three cases using atlas based parcellation and SPM5, and were compared to 10 randomly selected cases of FTLD-TDP and 10 randomly selected cases of FTLD-TAU. Total grey matter volumes were also calculated for all cases.
The FTLD-FUS cases had significantly smaller caudate volumes (p=0.02) yet similar frontal lobe grey matter volumes (p=0.12) compared to FTLD-TDP and FTLD-TAU. Caudate volumes when corrected for total grey matter volume (p=0.01) or frontal lobe grey matter volume (p=0.01) were significantly smaller in FTLD-FUS than FTLD-TDP and FTLD-TAU, and showed no overlap with the other two groups.
Caudate atrophy on MRI appears to be significantly greater in FTLD-FUS compared with FTLD-TDP and FTLD-TAU suggesting that severe caudate atrophy may be a useful clinical feature to predict FTLD-FUS pathology.
TDP-43; FTLD-TAU; FTLD-FUS; atlas based parcellation; caudate atrophy
To investigate associations of the Mediterranean diet (MeDi) components and the MeDi score with mild cognitive impairment (MCI).
Participants (aged 70–89 years) were clinically evaluated to assess MCI and dementia, and completed a 128-item food frequency questionnaire.
163 of 1,233 nondemented persons had MCI. The odds ratio of MCI was reduced for high vegetable intake [0.66 (95% CI = 0.44–0.99), p = 0.05] and for high mono-plus polyunsaturated fatty acid to saturated fatty acid ratio [0.52 (95% CI = 0.33–0.81), p = 0.007], adjusted for confounders. The risk of incident MCI or dementia was reduced in subjects with a high MeDi score [hazard ratio = 0.75 (95% CI = 0.46–1.21), p = 0.24].
Vegetables, unsaturated fats, and a high MeDi score may be beneficial to cognitive function.
Mild cognitive impairment; Dietary intake; Moderate alcohol intake; Unsaturated fatty acids; Mediterranean diet; Longitudinal; Prevalence studies; Incidence studies; Population-based
The clinical diagnosis of Alzheimer Disease (AD) does not exactly match the pathological findings at autopsy in every subject. Therefore, in-vivo imaging measures, such as Magnetic Resonance Imaging (MRI) that measure anatomical variations in each brain due to atrophy, would be clinically useful independent supplementary measures of pathology. We have developed an algorithm that extracts atrophy information from individual patient’s 3D MRI scans and assigns a STructural Abnormality iNDex (STAND)-score to the scan based on the degree of atrophy in comparison to patterns extracted from a large library of clinically well characterized AD and CN (cognitively normal) subject’s MRI scans. STAND-scores can be adjusted for demographics to give adjusted-STAND (aSTAND)-scores which are typically > 0 for subjects with abnormal brains. Since histopathological findings are considered to represent the “ground truth”, our objective was to assess the sensitivity of aSTAND-scores to pathological AD staging. This was done by comparing antemortem MRI based aSTAND-scores with post mortem grading of disease severity in 101 subjects who had both antemortem MRI and postmortem Braak neurofibrillary tangle (NFT) staging. We found a rank correlation of 0.62 (p<0.0001) between Braak NFT stage and aSTAND-scores. The results show that optimally extracted information from MRI scans such as STAND-scores accurately capture disease severity and can be used as an independent approximate surrogate marker for in-vivo pathological staging as well as for early identification of AD in individual subjects.
Alzheimer Disease; neurofibrillary tangles; amnestic mild cognitive impairment; Braak NFT stage; magnetic resonance imaging
In the past 10 years, there has been a virtual explosion in the literature concerning the construct of mild cognitive impairment. The interest in this topic demonstrates the increasing emphasis on the identification of the earliest features of cognitive disorders such as Alzheimer’s disease and other dementias. Mild cognitive impairment represents the earliest clinical features of these conditions and, hence, has become a focus of clinical, epidemiological, neuroimaging, biomarker, neuropathological, disease mechanism and clinical trials research. This review summarizes the progress that has been made while also recognizing the challenges that remain.
Mild cognitive impairment; Alzheimer’s disease; Imaging; Cognitive decline
Defining the nature of the contribution of stroke to cognitive impairment remains challenging.
We randomly selected Olmsted County, MN residents aged 70–89 years on October 1, 2004 and invited eligible non-demented subjects to participate. Participants (n = 2,050) were evaluated with an informant interview, a neurological evaluation, and neuropsychological testing. Neuropsychological testing included 9 tests to assess memory, attention and executive function, visuospatial cognition and language. Subjects were diagnosed by consensus as cognitively normal, MCI (either amnestic (a-) or non-amnestic (na-)), or dementia. A history of stroke was obtained from the subject and confirmed in the medical record. We computed the odds ratios (OR) for a clinical diagnosis of MCI or for scoring in the lowest quartile on each cognitive domain.
There were 1640 cognitively normal and 329 MCI subjects, 241 a-MCI and 88 na-MCI. In fully adjusted models with non-demented subjects only, a history of stroke was associated with a higher odds ratio (OR) of na-MCI (OR= 2.85, 95% CI 1.61 – 5.04) than a-MCI (OR= 1.77, 95% CI 1.14 – 2.74). A history of stroke was also associated with impaired function in each cognitive domain except memory. The association was strongest for attention and executive function (OR=2.48, 95% CI 1.73 – 3.53). APOE e4 genotype was associated only with a-MCI and with impaired memory function.
In this population-based sample of non-demented persons, a history of stroke was particularly associated with na-MCI and with impairment in non-memory cognition. APOE e4 genotype was associated with memory impairment and a-MCI.