Summary Background Three subtypes of Alzheimer's disease (AD) have been pathologically defined on the basis of the distribution of neurofibrillary tangles: typical AD, hippocampal-sparing AD, and ...limbic-predominant AD. Compared with typical AD, hippocampal-sparing AD has more neurofibrillary tangles in the cortex and fewer in the hippocampus, whereas the opposite pattern is seen in limbic-predominant AD. We aimed to determine whether MRI patterns of atrophy differ between these subtypes and whether structural neuroimaging could be a useful predictor of pathological subtype at autopsy. Methods We identified patients who had been followed up in the Mayo Clinic Alzheimer's Disease Research Center (Rochester, MN, USA) or in the Alzheimer's Disease Patient Registry (Rochester, MN, USA) between 1992 and 2005. To be eligible for inclusion, participants had to have had dementia, AD pathology at autopsy (Braak stage ≥IV and intermediate to high probability of AD), and an ante-mortem MRI. Cases were assigned to one of three pathological subtypes—hippocampal-sparing, limbic-predominant, and typical AD—on the basis of neurofibrillary tangle counts in hippocampus and cortex and ratio of hippocampal to cortical burden, without reference to neuronal loss. Voxel-based morphometry and atlas-based parcellation were used to compare patterns of grey matter loss between groups and with age-matched control individuals. Neuroimaging was obtained at the time of first presentation. To summarise pair-wise group differences, we report the area under the receiver operator characteristic curve (AUROC). Findings Of 177 eligible patients, 125 (71%) were classified as having typical AD, 33 (19%) as having limbic-predominant AD, and 19 (11%) as having hippocampal-sparing AD. Most patients with typical (98 78%) and limbic-predominant AD (31 94%) initially presented with an amnestic syndrome, but fewer patients with hippocampal-sparing AD (eight 42%) did. The most severe medial temporal atrophy was recorded in patients with limbic-predominant AD, followed by those with typical disease, and then those with hippocampal-sparing AD. Conversely, the most severe cortical atrophy was noted in patients with hippocampal-sparing AD, followed by those with typical disease, and then limbic-predominant AD. The ratio of hippocampal to cortical volumes allowed the best discrimination between subtypes (p<0·0001; three-way AUROC 0·52 95% CI 0·47–0·52; ratio of AUROC to chance classification 3·1 2·8–3·1). Patients with typical AD and non-amnesic initial presentation had a significantly higher ratio of hippocampal to cortical volumes (median 0·045 IQR 0·035–0·056) than did those with an amnesic presentation (0·041 0·031–0·057; p=0·001). Interpretation Patterns of atrophy on MRI differ across the pathological subtypes of AD. MRI regional volumetric analysis can reliably track the distribution of neurofibrillary tangle pathology and can predict pathological subtype of AD at autopsy. Funding US National Institutes of Health (National Institute on Aging).
Abstract Introduction Our goal was to develop cut points for amyloid positron emission tomography (PET), tau PET, flouro-deoxyglucose (FDG) PET, and MRI cortical thickness. Methods We examined five ...methods for determining cut points. Results The reliable worsening method produced a cut point only for amyloid PET. The specificity, sensitivity, and accuracy of cognitively impaired versus young clinically normal (CN) methods labeled the most people abnormal and all gave similar cut points for tau PET, FDG PET, and cortical thickness. Cut points defined using the accuracy of cognitively impaired versus age-matched CN method labeled fewer people abnormal. Discussion In the future, we will use a single cut point for amyloid PET (standardized uptake value ratio, 1.42; centiloid, 19) based on the reliable worsening cut point method. We will base lenient cut points for tau PET, FDG PET, and cortical thickness on the accuracy of cognitively impaired versus young CN method and base conservative cut points on the accuracy of cognitively impaired versus age-matched CN method.
Summary Background A new classification for biomarkers in Alzheimer's disease and cognitive ageing research is based on grouping the markers into three categories: amyloid deposition (A), tauopathy ...(T), and neurodegeneration or neuronal injury (N). Dichotomising these biomarkers as normal or abnormal results in eight possible profiles. We determined the clinical characteristics and prevalence of each ATN profile in cognitively unimpaired individuals aged 50 years and older. Methods All participants were in the Mayo Clinic Study of Aging, a population-based study that uses a medical records linkage system to enumerate all individuals aged 50–89 years in Olmsted County, MN, USA. Potential participants are randomly selected, stratified by age and sex, and invited to participate in cognitive assessments; individuals without medical contraindications are invited to participate in brain imaging studies. Participants who were judged clinically as having no cognitive impairment and underwent multimodality imaging between Oct 11, 2006, and Oct 5, 2016, were included in the current study. Participants were classified as having normal (A−) or abnormal (A+) amyloid using amyloid PET, normal (T−) or abnormal (T+) tau using tau PET, and normal (N−) or abnormal (N+) neurodegeneration or neuronal injury using cortical thickness assessed by MRI. We used the cutoff points of standard uptake value ratio (SUVR) 1·42 (centiloid 19) for amyloid PET, 1·23 SUVR for tau PET, and 2·67 mm for MRI cortical thickness. Age-specific and sex-specific prevalences of the eight groups were determined using multinomial models combining data from 435 individuals with amyloid PET, tau PET, and MRI assessments, and 1113 individuals who underwent amyloid PET and MRI, but not tau PET imaging. Findings The numbers of participants in each profile group were 165 A−T−N−, 35 A−T+N−, 63 A−T−N+, 19 A−T+N+, 44 A+T−N−, 25 A+T+N−, 35 A+T−N+, and 49 A+T+N+. Age differed by ATN group (p<0·0001), ranging from a median 58 years (IQR 55–64) in A–T–N– and 57 years (54–64) in A–T+N– to a median 80 years (75–84) in A+T–N+ and 79 years (73–87) in A+T+N+. The number of APOE ε4 carriers differed by ATN group (p=0·04), with carriers roughly twice as frequent in each A+ group versus the corresponding A– group. White matter hyperintensity volume (p<0·0001) and cognitive performance (p<0·0001) also differed by ATN group. Tau PET and neurodegeneration biomarkers were discordant in most individuals who would be categorised as stage 2 or 3 preclinical Alzheimer's disease (A+T+N−, A+T−N+, and A+T+N+; 86% at age 65 years and 51% at age 80 years) or with suspected non-Alzheimer's pathophysiology (A−T+N−, A−T−N+, and A−T+N+; 92% at age 65 years and 78% at age 80 years). From age 50 years, A−T−N− prevalence declined and A+T+N+ and A−T+N+ prevalence increased. In both men and women, A−T−N− was the most prevalent until age late 70s. After about age 80 years, A+T+N+ was most prevalent. By age 85 years, more than 90% of men and women had one or more biomarker abnormalities. Interpretation Biomarkers of fibrillar tau deposition can be included with those of β-amyloidosis and neurodegeneration or neuronal injury to more fully characterise the heterogeneous pathological profiles in the population. Both amyloid- dependent and amyloid-independent pathological profiles can be identified in the cognitively unimpaired population. The prevalence of each ATN group changed substantially with age, with progression towards more biomarker abnormalities among individuals who remained cognitively unimpaired. Funding National Institute on Aging (part of the US National Institutes of Health), the Alexander Family Professorship of Alzheimer's Disease Research, the Mayo Clinic, and the GHR Foundation.
Summary In 2010, we put forward a hypothetical model of the major biomarkers of Alzheimer's disease (AD). The model was received with interest because we described the temporal evolution of AD ...biomarkers in relation to each other and to the onset and progression of clinical symptoms. Since then, evidence has accumulated that supports the major assumptions of this model. Evidence has also appeared that challenges some of our assumptions, which has allowed us to modify our original model. Refinements to our model include indexing of individuals by time rather than clinical symptom severity; incorporation of interindividual variability in cognitive impairment associated with progression of AD pathophysiology; modifications of the specific temporal ordering of some biomarkers; and recognition that the two major proteinopathies underlying AD biomarker changes, amyloid β (Aβ) and tau, might be initiated independently in sporadic AD, in which we hypothesise that an incident Aβ pathophysiology can accelerate antecedent limbic and brainstem tauopathy.
Objective:
A workgroup commissioned by the Alzheimer's Association (AA) and the National Institute on Aging (NIA) recently published research criteria for preclinical Alzheimer 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 cutpoints. A group of 450 cognitively normal (CN) subjects from a population‐based sample was used to develop cognitive cutpoints and to assess population frequencies of the different preclinical AD stages using different cutpoint criteria.
Results:
The new criteria subdivide the preclinical phase of AD into stages 1 to 3. To classify our CN subjects, 2 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 cutpoints 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 only 3% unclassified. Future longitudinal validation of the criteria will be important ANN NEUROL 2012;
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.
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).
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.
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.).
Summary Background As preclinical Alzheimer's disease becomes a target for therapeutic intervention, the overlap between imaging abnormalities associated with typical ageing and those associated with ...Alzheimer's disease needs to be recognised. We aimed to characterise how typical ageing and preclinical Alzheimer's disease overlap in terms of β-amyloidosis and neurodegeneration. Methods We measured age-specific frequencies of amyloidosis and neurodegeneration in individuals with normal cognitive function aged 50–89 years. Potential participants were randomly selected from the Olmsted County (MN, USA) population-based study of cognitive ageing and invited to participate in cognitive and imaging assessments. To be eligible for inclusion, individuals must have been judged clinically to have no cognitive impairment and have undergone amyloid PET,18 F-fluorodeoxyglucose (18 F-FDG) PET, and MRI. Imaging results were obtained from March 28, 2006, to Dec 3, 2013. Amyloid status (positive A+ or negative A– ) was determined by amyloid PET with11 C Pittsburgh compound B. Neurodegeneration status (positive N+ or negative N– ) was determined by an Alzheimer's disease signature18 F-FDG PET or hippocampal volume on MRI. We determined age-specific frequencies of the four groups (amyloid negative and neurodegeneration negative A– N– , amyloid positive and neurodegeneration negative A+ N– , amyloid negative and neurodegeneration positive A– N+ , or amyloid positive and neurodegeneration positive A+ N+ ) cross-sectionally using multinomial regression models. We also investigated associations of group frequencies with APOE ɛ4 status (assessed with DNA extracted from blood) and sex by including these covariates in the multinomial models. Findings The study population consisted of 985 eligible participants. The population frequency of A– N– was 100% (n=985) at age 50 years and fell to 17% (95% CI 11–24) by age 89 years. The frequency of A+ N– increased to 28% (24–32) at age 74 years, then decreased to 17% (11–25) by age 89 years. The frequency of A– N+ increased from age 60 years, reaching 24% (16–34) by age 89 years. The frequency of A+ N+ increased from age 65 years, reaching 42% (31–52) by age 89 years. The results from our multinomial models suggest that A+ N– and A+ N+ were more frequent in APOE ɛ4 carriers than in non-carriers and that A+ N+ was more, and A+ N– less frequent in men than in women. Interpretation Accumulation of amyloid and neurodegeneration are nearly inevitable by old age, but many people are able to maintain normal cognitive function despite these imaging abnormalities. Changes in the frequency of amyloidosis and neurodegeneration with age, which seem to be modified by APOE ɛ4 and sex, suggest that pathophysiological sequences might differ between individuals. Funding US National Institute on Aging and Alexander Family Professorship of Alzheimer's Disease Research.
Summary Background In a 2014 cross-sectional analysis, we showed that amyloid and neurodegeneration biomarker states in participants with no clinical impairment varied greatly with age, suggesting ...dynamic within-person processes. In this longitudinal study, we aimed to estimate rates of transition from a less to a more abnormal biomarker state by age in individuals without dementia, as well as to assess rates of transition to dementia from an abnormal state. Methods Participants from the Mayo Clinic Study of Aging (Olmsted County, MN, USA) without dementia at baseline were included in this study, a subset of whom agreed to multimodality imaging. Amyloid PET (with11 C-Pittsburgh compound B) was used to classify individuals as amyloid positive (A+ ) or negative (A− ).18 F-fluorodeoxyglucose (18 F-FDG)-PET and MRI were used to classify individuals as neurodegeneration positive (N+ ) or negative (N− ). We used all observations, including those from participants who did not have imaging results, to construct a multistate Markov model to estimate four different age-specific biomarker state transition rates: A− N− to A+ N− ; A− N− to A− N+ (suspected non-Alzheimer's pathology); A+ N− to A+ N+ ; and A− N+ to A+ N+ . We also estimated two age-specific rates to dementia: A+ N+ to dementia and A− N+ to dementia. Using these state-to-state transition rates, we estimated biomarker state frequencies by age. Findings At baseline (between Nov 29, 2004, to March 7, 2015), 4049 participants did not have dementia (3512 87% were clinically normal and 537 13% had mild cognitive impairment). 1541 individuals underwent imaging between March 28, 2006, to April 30, 2015. Transition rates were low at age 50 years and, with one exception, exponentially increased with age. At age 85 years compared with age 65 years, the rate was nearly 11-times higher (17·2 vs 1·6 per 100 person-years) for the transition from A− N− to A− N+ , three-times higher (20·8 vs 6·1) for A+ N− to A+ N+ , and five-times higher (13·2 vs 2·6) for A− N+ to A+ N+ . The rate of transition was also increased at age 85 years compared with age 65 years for A+ N+ to dementia (7·0 vs 0·8) and for A− N+ to dementia (1·7 vs 0·6). The one exception to an exponential increase with age was the transition rate from A− N− to A+ N− , which increased from 4·0 transitions per 100 person-years at age 65 years to 6·9 transitions per 100 person-years at age 75 and then plateaued beyond that age. Estimated biomarker frequencies by age from the multistate model were similar to cross-sectional biomarker frequencies. Interpretation Our transition rates suggest that brain ageing is a nearly inevitable acceleration toward worse biomarker and clinical states. The one exception is the transition to amyloidosis without neurodegeneration, which is most dynamic from age 60 years to 70 years and then plateaus beyond that age. We found that simple transition rates can explain complex, highly interdependent biomarker state frequencies in our population. Funding National Institute on Aging, Alexander Family Professorship of Alzheimer's Disease Research, the GHR Foundation.
The logopenic variant of primary progressive aphasia is an atypical clinical variant of Alzheimer's disease which is typically characterized by left temporoparietal atrophy on magnetic resonance ...imaging and hypometabolism on F-18 fluorodeoxyglucose positron emission tomography. We aimed to characterize and compare patterns of atrophy and hypometabolism in logopenic primary progressive aphasia, and determine which brain regions and imaging modality best differentiates logopenic primary progressive aphasia from typical dementia of the Alzheimer's type.
A total of 27 logopenic primary progressive aphasia subjects underwent fluorodeoxyglucose positron emission tomography and volumetric magnetic resonance imaging. These subjects were matched to 27 controls and 27 subjects with dementia of the Alzheimer's type. Patterns of atrophy and hypometabolism were assessed at the voxel and region-level using Statistical Parametric Mapping. Penalized logistic regression analysis was used to determine what combinations of regions best discriminate between groups.
Atrophy and hypometabolism was observed in lateral temporoparietal and medial parietal lobes, left greater than right, and left frontal lobe in the logopenic group. The logopenic group showed greater left inferior, middle and superior lateral temporal atrophy (inferior p = 0.02; middle p = 0.007, superior p = 0.002) and hypometabolism (inferior p = 0.006, middle p = 0.002, superior p = 0.001), and less right medial temporal atrophy (p = 0.02) and hypometabolism (p<0.001), and right posterior cingulate hypometabolism (p<0.001) than dementia of the Alzheimer's type. An age-adjusted penalized logistic model incorporating atrophy and hypometabolism achieved excellent discrimination (area under the receiver operator characteristic curve = 0.89) between logopenic and dementia of the Alzheimer's type subjects, with optimal discrimination achieved using right medial temporal and posterior cingulate hypometabolism, left inferior, middle and superior temporal hypometabolism, and left superior temporal volume.
Patterns of atrophy and hypometabolism both differ between logopenic primary progressive aphasia and dementia of the Alzheimer's type and both modalities provide excellent discrimination between groups.
Objective
An extensive analysis of white matter plaques in a large sample of multiple sclerosis (MS) autopsies provides insights into the dynamic nature of MS pathology.
Methods
One hundred twenty MS ...cases (1,220 tissue blocks) were included. Plaque types were classified according to demyelinating activity based on stringent criteria. Early active, late active, smoldering, inactive, and shadow plaques were distinguished. A total of 2,476 MS white matter plaques were identified. Plaque type distribution was analyzed in relation to clinical data.
Results
Active plaques were most often found in early disease, whereas at later stages, smoldering, inactive, and shadow plaques predominated. The presence of early active plaques rapidly declined with disease duration. Plaque type distribution differed significantly by clinical course. The majority of plaques in acute monophasic and relapsing–remitting MS (RRMS) were active. Among secondary progressive MS (SPMS) cases with attacks, all plaque types could be distinguished including active plaques, in contrast to SPMS without attacks, in which inactive plaques predominated. Smoldering plaques were frequently and almost exclusively found in progressive MS. At 47 years of age, an equilibrium was observed between active and inactive plaques, whereas smoldering plaques began to peak. Men displayed a higher proportion of smoldering plaques.
Interpretation
Disease duration, clinical course, age, and gender contribute to the dynamic nature of white matter MS pathology. Active MS plaques predominate in acute and early RRMS and are the likely substrate of clinical attacks. Progressive MS transitions to an accumulation of smoldering plaques characterized by microglial activation and slow expansion of pre‐existing plaques. Whether current MS therapeutics impact this pathological driver of disease progression remains uncertain. Ann Neurol 2015;78:Ann Neurol 2015;78:679–696
PDF
