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.
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 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).
Summary Background Neurofibrillary pathology has a stereotypical progression in Alzheimer's disease (AD) that is encapsulated in the Braak staging scheme; however, some AD cases are atypical and do ...not fit into this scheme. We aimed to compare clinical and neuropathological features between typical and atypical AD cases. Methods AD cases with a Braak neurofibrillary tangle stage of more than IV were identified from a brain bank database. By use of thioflavin-S fluorescence microscopy, we assessed the density and the distribution of neurofibrillary tangles in three cortical regions and two hippocampal sectors. These data were used to construct an algorithm to classify AD cases into typical, hippocampal sparing, or limbic predominant. Classified cases were then compared for clinical, demographic, pathological, and genetic characteristics. An independent cohort of AD cases was assessed to validate findings from the initial cohort. Findings 889 cases of AD, 398 men and 491 women with age at death of 37–103 years, were classified with the algorithm as hippocampal sparing (97 cases 11%), typical (665 75%), or limbic predominant (127 14%). By comparison with typical AD, neurofibrillary tangle counts per 0.125 mm2 in hippocampal sparing cases were higher in cortical areas (median 13, IQR 11–16) and lower in the hippocampus (7.5, 5.2–9.5), whereas counts in limbic-predominant cases were lower in cortical areas (4.3, 3.0–5.7) and higher in the hippocampus (27, 22–35). Hippocampal sparing cases had less hippocampal atrophy than did typical and limbic-predominant cases. Patients with hippocampal sparing AD were younger at death (mean 72 years SD 10) and a higher proportion of them were men (61 63%), whereas those with limbic-predominant AD were older (mean 86 years SD 6) and a higher proportion of them were women (87 69%). Microtubule-associated protein tau ( MAPT ) H1H1 genotype was more common in limbic-predominant AD (54 70%) than in hippocampal sparing AD (24 46%; p=0.011), but did not differ significantly between limbic-predominant and typical AD (204 59%; p=0.11). Apolipoprotein E ( APOE ) ε4 allele status differed between AD subtypes only when data were stratified by age at onset. Clinical presentation, age at onset, disease duration, and rate of cognitive decline differed between the AD subtypes. These findings were confirmed in a validation cohort of 113 patients with AD. Interpretation These data support the hypothesis that AD has distinct clinicopathological subtypes. Hippocampal sparing and limbic-predominant AD subtypes might account for about 25% of cases, and hence should be considered when designing clinical, genetic, biomarker, and treatment studies in patients with AD. Funding US National Institutes of Health via Mayo Alzheimer's Disease Research Center, Mayo Clinic Study on Aging, Florida Alzheimer's Disease Research Center, and Einstein Aging Study; and State of Florida Alzheimer's Disease Initiative.
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.
Summary Background Hexanucleotide repeat expansions in chromosome 9 open reading frame 72 ( C9ORF72 ) are the most common known genetic cause of frontotemporal dementia (FTD) and motor neuron disease ...(MND). We assessed whether expansion size is associated with disease severity or phenotype. Methods We did a cross-sectional Southern blot characterisation study (Xpansize-72) in a cohort of individuals with FTD, MND, both these diseases, or no clinical phenotype. All participants had GGGGCC repeat expansions in C9ORF72 , and high quality DNA was available from one or more of the frontal cortex, cerebellum, or blood. We used Southern blotting techniques and densitometry to estimate the repeat size of the most abundant expansion species. We compared repeat sizes between different tissues using Wilcoxon rank sum and Wilcoxon signed rank tests, and between disease subgroups using Kruskal-Wallis rank sum tests. We assessed the association of repeat size with age at onset and age at collection using a Spearman's test of correlation, and assessed the association between repeat size and survival after disease onset using Cox proportional hazards regression models. Findings We included 84 individuals with C9ORF72 expansions: 35 had FTD, 16 had FTD and MND, 30 had MND, and three had no clinical phenotype. We focused our analysis on three major tissue subgroups: frontal cortex (available from 41 patients 21 with FTD, 11 with FTD and MND, and nine with MND), cerebellum (40 patients 20 with FTD, 12 with FTD and MND, and eight with MND), and blood (47 patients 15 with FTD, nine with FTD and MND, and 23 with MND and three carriers who had no clinical phenotype). Repeat lengths in the cerebellum were smaller (median 12·3 kb about 1667 repeat units, IQR 11·1–14·3) than those in the frontal cortex (33·8 kb about 5250 repeat units, 23·5–44·9; p<0·0001) and those in blood (18·6 kb about 2717 repeat units, 13·9–28·1; p=0·0002). Within these tissues, we detected no difference in repeat length between disease subgroups (cerebellum p=0·96, frontal cortex p=0·27, blood p=0·10). In the frontal cortex of patients with FTD, repeat length correlated with age at onset ( r =0·63; p=0·003) and age at sample collection ( r =0·58; p=0·006); we did not detect such a correlation in samples from the cerebellum or blood. When assessing cerebellum samples from the overall cohort, survival after disease onset was 4·8 years (IQR 3·0–7·4) in the group with expansions greater than 1467 repeat units (the 25th percentile of repeat lengths) versus 7·4 years (6·3–10·9) in the group with smaller expansions (HR 3·27, 95% CI 1·34–7·95; p=0·009). Interpretation We detected substantial variation in repeat sizes between samples from the cerebellum, frontal cortex, and blood, and longer repeat sizes in the cerebellum seem to be associated with a survival disadvantage. Our findings indicate that expansion size does affect disease severity, which—if replicated in other cohorts—could be relevant for genetic counselling. Funding The ALS Therapy Alliance, the National Institute of Neurological Disorders and Stroke, the National Institute on Aging, the Arizona Department of Health Services, the Arizona Biomedical Research Commission, and the Michael J Fox Foundation for Parkinson's Research.
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