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.
To increase the opportunity to delay or prevent mild cognitive impairment (MCI) or Alzheimer disease (AD) dementia, markers of early detection are essential. Olfactory impairment may be an important ...clinical marker and predictor of these conditions and may help identify persons at increased risk.
To examine associations of impaired olfaction with incident MCI subtypes and progression from MCI subtypes to AD dementia.
Participants enrolled in the population-based, prospective Mayo Clinic Study of Aging between 2004 and 2010 were clinically evaluated at baseline and every 15 months through 2014. Participants (N = 1630) were classified as having normal cognition, MCI (amnestic MCI aMCI and nonamnestic MCI naMCI), and dementia. We administered the Brief Smell Identification Test (B-SIT) to assess olfactory function.
Mild cognitive impairment, AD dementia, and longitudinal change in cognitive performance measures.
Of the 1630 participants who were cognitively normal at the time of the smell test, 33 died before follow-up and 167 were lost to follow-up. Among the 1430 cognitively normal participants included, the mean (SD) age was 79.5 (5.3) years, 49.4% were men, the mean duration of education was 14.3 years, and 25.4% were APOE ε4 carriers. Over a mean 3.5 years of follow-up, there were 250 incident cases of MCI among 1430 cognitively normal participants. We observed an association between decreasing olfactory identification, as measured by a decrease in the number of correct responses in B-SIT score, and an increased risk of aMCI. Compared with the upper B-SIT quartile (quartile Q 4, best scores), hazard ratios (HRs) (95% CI) were 1.12 (0.65-1.92) for Q3 (P = .68); 1.95 (1.25-3.03) for Q2 (P = .003); and 2.18 (1.36-3.51) for Q1 (P = .001) (worst scores; P for trend <.001) after adjustment for sex and education, with age as the time scale. There was no association with naMCI. There were 64 incident dementia cases among 221 prevalent MCI cases. The B-SIT score also predicted progression from aMCI to AD dementia, with a significant dose-response with worsening B-SIT quartiles. Compared with Q4, HR (95% CI) estimates were 3.02 (1.06-8.57) for Q3 (P = .04); 3.63 (1.19-11.10) for Q2 (P = .02); and 5.20 (1.90-14.20) for Q1 (P = .001). After adjusting for key predictors of MCI risk, B-SIT (as a continuous measure) remained a significant predictor of MCI (HR, 1.10 95% CI, 1.04-1.16; P < .001) and improved the model concordance.
Olfactory impairment is associated with incident aMCI and progression from aMCI to AD dementia. These findings are consistent with previous studies that have reported associations of olfactory impairment with cognitive impairment in late life and suggest that olfactory tests have potential utility for screening for MCI and MCI that is likely to progress.
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.
Objective
To investigate the associations between age, vascular health, and Alzheimer disease (AD) imaging biomarkers in an elderly sample.
Methods
We identified 430 individuals along the cognitive ...continuum aged >60 years with amyloid positron emission tomography (PET), tau PET, and magnetic resonance imaging (MRI) scans from the population‐based Mayo Clinic Study of Aging. A subset of 329 individuals had fluorodeoxyglucose (FDG) PET. We ascertained presently existing cardiovascular and metabolic conditions (CMC) from health care records and used the summation of presence/absence of hypertension, hyperlipidemia, cardiac arrhythmias, coronary artery disease, congestive heart failure, diabetes mellitus, and stroke as a surrogate for vascular health. We used global amyloid from Pittsburgh compound B PET, entorhinal cortex tau uptake (ERC‐tau) from tau‐PET, and neurodegeneration in AD signature regions from MRI and FDG‐PET as surrogates for AD pathophysiology. We dichotomized participants into CMC = 0 (CMC−) versus CMC > 0 (CMC+) and tested for age‐adjusted group differences in AD biomarkers. Using structural equation models (SEMs), we assessed the impact of vascular health on AD biomarker cascade (amyloid leads to tau leads to neurodegeneration) after considering the direct and indirect age, sex, and apolipoprotein E effects.
Results
CMC+ participants had significantly greater neurodegeneration than CMC− participants but did not differ by amyloid or ERC‐tau. The SEMs showed that (1) vascular health had a significant direct and indirect impact on neurodegeneration but not on amyloid; and (2) vascular health, specifically the presence of hyperlipidemia, had a significant direct impact on ERC‐tau.
Interpretation
Vascular health had quantifiably greater impact on neurodegeneration in AD regions than on amyloid deposition. Longitudinal studies are warranted to clarify the relationship between tau deposition and vascular health. Ann Neurol 2017;82:706–718
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;
The authors conducted a prospective cohort study to estimate the risk of incident mild cognitive impairment in cognitively normal elderly (aged ≥70 years) individuals with or without neuropsychiatric ...symptoms at baseline. The research was conducted in the setting of the population-based Mayo Clinic Study of Aging.
A classification of normal cognitive aging, mild cognitive impairment, and dementia was adjudicated by an expert consensus panel based on published criteria. Hazard ratios and 95% confidence intervals were computed using Cox proportional hazards model, with age as a time scale. Baseline Neuropsychiatric Inventory Questionnaire data were available for 1,587 cognitively normal persons who underwent at least one follow-up visit.
The cohort was followed to incident mild cognitive impairment (N=365) or censoring variables (N=179) for a median of 5 years. Agitation (hazard ratio=3.06, 95% CI=1.89-4.93), apathy (hazard ratio=2.26, 95% CI=1.49-3.41), anxiety (hazard ratio=1.87, 95% CI=1.28-2.73), irritability (hazard ratio=1.84, 95% CI=1.31-2.58), and depression (hazard ratio=1.63, 95% CI=1.23-2.16), observed initially, increased risk for later mild cognitive impairment. Delusion and hallucination did not. A secondary analysis, limited in significance by the small number of study participants, showed that euphoria, disinhibition, and nighttime behaviors were significant predictors of nonamnestic mild cognitive impairment but not amnestic mild cognitive impairment. By contrast, depression predicted amnestic mild cognitive impairment (hazard ratio=1.74, 95% CI=1.22-2.47) but not nonamnestic mild cognitive impairment.
An increased incidence of mild cognitive impairment was observed in community-dwelling elderly adults who had nonpsychotic psychiatric symptoms at baseline. These baseline psychiatric symptoms were of similar or greater magnitude as biomarkers (genetic and structural MRI) in increasing the risk of incident mild cognitive impairment.
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.
To conduct a systematic review of all studies to determine whether there is an association between the Mediterranean diet (MeDi) and cognitive impairment.
We conducted a comprehensive search of the ...major databases and hand-searched proceedings of major neurology, psychiatry, and dementia conferences through November 2012. Prospective cohort studies examining the MeDi with longitudinal follow-up of at least 1 year and reporting cognitive outcomes (mild cognitive impairment MCI or Alzheimer's disease AD) were included. The effect size was estimated as hazard-ratio (HR) with 95% confidence intervals (CIs) using the random-effects model. Heterogeneity was assessed using Cochran's Q-test and I2-statistic.
Out of the 664 studies screened, five studies met eligibility criteria. Higher adherence to the MeDi was associated with reduced risk of MCI and AD. The subjects in the highest MeDi tertile had 33% less risk (adjusted HR = 0.67; 95% CI, 0.55-0.81; p < 0.0001) of cognitive impairment (MCI or AD) as compared to the lowest MeDi score tertile. Among cognitively normal individuals, higher adherence to the MeDi was associated with a reduced risk of MCI (HR = 0.73; 95% CI, 0.56-0.96; p = 0.02) and AD (HR = 0.64; 95% CI, 0.46-0.89; p = 0.007). There was no significant heterogeneity in the analyses.
While the overall number of studies is small, pooled results suggest that a higher adherence to the MeDi is associated with a reduced risk of developing MCI and AD, and a reduced risk of progressing from MCI to AD. Further prospective-cohort studies with longer follow-up and randomized controlled trials are warranted to consolidate the evidence. Systematic review registration number: PROSPERO 2013: CRD42013003868.
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