Alzheimer's Disease Neuroimaging Initiative Mild Cognitive Impairment Research Articles

Prescribing cholinesterase inhibitors in mild cognitive impairment-Observations from the Alzheimer's Disease Neuroimaging Initiative.

IntroductionAnalyses of off‐label use of acetylcholinesterase inhibitors (AChEIs) in mild cognitive impairment (MCI) has produced mixed results. Post hoc analyses of observational cohorts, such as the Alzheimer's Disease Neuroimaging Initiative (ADNI), have reported deleterious effects in AChEI‐treated subjects (AChEI+). Here, we used neuroimaging biomarkers to determine whether AChEI+ subjects had a greater rate of neurodegeneration than untreated (AChEI–) subjects while accounting for baseline differences.MethodsWe selected 121 ADNI MCI AChEI+ subjects and 151 AChEI– subjects with a magnetic resonance imaging (MRI) scan; 82 AChEI+ and 110 AChEI– also had a fluorodeoxyglucose (FDG) scan. A subset (83 AChEI+ and 98 AChEI–) had cerebrospinal fluid (CSF) or amyloid positron emission tomography (PET) assessment for amyloid positivity. Linear regression models were used to compare the effect of treatment on changes in Mini‐Mental State Examination and Clinical Dementia Rating‐Sum of Boxes scores. We used standard regression in SPM (for baseline) and the SPM toolbox sandwich estimator, SwE (for longitudinal) for comparisons of AChEI+ and AChEI– FDG PET and MRI data.ResultsAt baseline, the AChEI+ group had significantly reduced cortical gray matter density (GMD) and more hypometabolism than AChEI– subjects. The greater rate of atrophy and hypometabolic changes over time in AChEI+ compared to AChEI– subjects did not survive correction for baseline differences. AChEI+ participants were more likely to be amyloid‐positive and have lower GMD and FDG standardized uptake value ratio than AChEI– at baseline. AChEI+ subjects showed greater atrophy over time, which remained significant after controlling for amyloid status.DiscussionOur data suggest that the observed differences in rates of cognitive decline, atrophy, and hypometabolism are likely the result of significant baseline differences between the groups. Furthermore, the data indicate no treatment effect of AChEI (positive of negative), rather that physicians prescribe AChEI to subjects who present with more severe clinical impairment. This alone may account for the negative effect seen previously in the ADNI population of AChEI use among MCI subjects.

High blood pressure predicts hippocampal atrophy rate in cognitively impaired elders.

IntroductionUnderstanding relationships among blood pressure (BP), cognition, and brain volume could inform Alzheimer's disease (AD) management.MethodsWe investigated Alzheimer's Disease Neuroimaging Initiative (ADNI) participants: 200 controls, 346 mild cognitive impairment (MCI), and 154 AD. National Alzheimer's Co‐ordinating Center (NACC) participants were separately analyzed: 1098 controls, 2297 MCI, and 4845 AD. Relationships between cognition and BP were assessed in both cohorts and BP and atrophy rates in ADNI. Multivariate mixed linear‐regression models were fitted with joint outcomes of BP (systolic, diastolic, and pulse pressure), cognition (Mini‐Mental State Examination, Logical Memory, and Digit Symbol) and atrophy rate (whole‐brain, hippocampus).ResultsADNI MCI and AD patients with greater baseline systolic BP had higher hippocampal atrophy rates ([r, P value]; 0.2, 0.005 and 0.2, 0.04, respectively). NACC AD patients with lower systolic BP had lower cognitive scores (0.1, 0.0003).DiscussionHigher late‐life BP may be associated with faster decline in cognitively impaired elders.

Early versus late MCI: Improved MCI staging using a neuropsychological approach

IntroductionThe Alzheimer's Disease Neuroimaging Initiative (ADNI) separates “early” and “late” mild cognitive impairment (MCI) based on a single memory test. We compared ADNI's MCI classifications to our neuropsychological approach, which more broadly assesses cognitive abilities. MethodsThree hundred thirty-six ADNI-2 participants were classified as “early” or “late” MCI. Cluster analysis was performed on neuropsychological test data, and participants were reclassified based on cluster results. These two staging approaches were compared on progression rates, cerebrospinal fluid biomarkers, and cortical thickness profiles. ResultsThere was little correspondence between the two staging methods. ADNI's early MCI group included a large proportion of false-positive diagnostic errors. The reclassified neuropsychological MCI groups showed steeper survival curves and more abnormal biomarkers. ConclusionsOur novel neuropsychological approach improved the staging of MCI by (1) capturing individuals at an early symptomatic stage, (2) minimizing false-positive cases, and (3) identifying a late MCI group further along the disease trajectory.

Artificially low mild cognitive impairment to normal reversion rate in the Alzheimer's Disease Neuroimaging Initiative

IntroductionWe examined reasons for low mild cognitive impairment (MCI)-to-cognitively normal (CN) reversion rates in the Alzheimer's Disease Neuroimaging Initiative (ADNI). MethodsCN and MCI participants were identified as remaining stable, progressing, or reverting at 1-year of follow-up (Year 1). Application of ADNI's MCI criteria at Year 1 in addition to Alzheimer's disease biomarkers by group were examined. ResultsThe MCI-to-CN reversion rate was 3.0%. When specific components were examined, 22.5% of stable MCI participants had normal memory performance at Year 1 and their Alzheimer's disease biomarkers were consistent with the stable CN group. At Year 1, when all MCI criteria were not met, the more subjective Clinical Dementia Rating rather than objective memory measure appeared to drive continuation of the MCI diagnosis. DiscussionResults demonstrate an artificially low 1-year MCI-to-CN reversion rate in ADNI-diagnosed participants. If the Logical Memory cutoffs had been consistently applied, the reversion rate would have been at least 21.8%.

Impact of plasma glucose level on the pattern of brain FDG uptake and the predictive power of FDG PET in mild cognitive impairment.

Increased blood glucose level (BGL) has been reported to cause alterations of FDG uptake in the brain that mimic Alzheimer's disease (AD), even within the "acceptable" range ≤ 160mg/dl. The aim of this study was (i) to confirm this in a large sample of well-characterized normal control (NC) subjects, and (ii) to analyze its impact on the prediction of AD dementia (ADD) in mild cognitive impairment (MCI). The study included NCs from the Alzheimer's Disease Neuroimaging Initiative (ADNI) that were cognitively stable for ≥36months after PET (n = 87, 74.2 ± 5.3 y), and ADNI MCIs with ≥36months follow-up if not progressed to ADD earlier (n = 323, 71.1 ± 7.1 y). Seventy-three of the MCIs had progressed to ADD within 36months. In the NCs, parenchyma-scaled FDG uptake was tested for clusters of correlation with BGL on the family-wise, error-corrected 5% level. In the MCIs, ROC analysis was used to assess the power of FDG uptake in a predefined AD-typical region for prediction of ADD. ROC analysis was repeated after correcting mean FDG uptake in the AD-typical region for BGL based on linear regression in the NCs. In the NCs, BGL (59-149mg/dl) was negatively correlated with FDG uptake in a cluster comprising the occipital cortex and precuneus but sparing the posterior cingulate, independent of amyloid-β and ApoE4 status. In the MCIs, FDG uptake in the AD-typical region provided an area of 0.804 under the ROC curve for prediction of ADD. Correcting FDG uptake in the AD-typical region for BGL (55-189mg/dl) did not change predictive performance (area = 0.808, p = 0.311). Increasing BGL is associated with relative reduction of FDG uptake in the posterior cortex even in the "acceptable" range ≤ 160mg/dl. The BGL-associated pattern is similar to the typical AD pattern, but not identical. BGL-associated variability of regional FDG uptake has no relevant impact on the power of FDG PET for prediction of MCI-to-ADD progression.

SUBJECTIVE COGNITIVE COMPLAINTS CONTRIBUTE TO MISDIAGNOSIS OF MILD COGNITIVE IMPAIRMENT

Subjective cognitive complaints are a criterion for the diagnosis of mild cognitive impairment (MCI), despite their uncertain relationship to objective memory performance in MCI. We aimed to examine self-reported cognitive complaints in subgroups of the Alzheimer's Disease Neuroimaging Initiative (ADNI) MCI cohort to determine whether they are a valuable inclusion in the diagnosis of MCI or, alternatively, if they contribute to misdiagnosis. Subgroups of MCI were derived using cluster analysis of baseline neuropsychological test data from 448 ADNI MCI participants. Cognitive complaints were assessed via the Everyday Cognition (ECog) questionnaire, and discrepancy scores were calculated between self- and informant-report. Cluster analysis revealed Amnestic and Mixed cognitive phenotypes as well as a third Cluster-Derived Normal subgroup (41.3%), whose neuropsychological and cerebrospinal fluid (CSF) Alzheimer's disease (AD) biomarker profiles did not differ from a robust normal control group. This cognitively intact phenotype of MCI participants overestimated their cognitive problems relative to their informant, whereas Amnestic MCI participants with objective memory impairment underestimated their cognitive problems. Underestimation of cognitive problems was associated with positive CSF AD biomarkers and progression to dementia. Overall, there was no relationship between self-reported cognitive complaints and objective cognitive functioning, but significant correlations were observed with depressive symptoms. The inclusion of self-reported complaints in MCI diagnostic criteria may cloud rather than clarify diagnosis and result in high rates of misclassification of MCI. Discrepancies between self- and informant-report demonstrate that overestimation of cognitive problems is characteristic of normal aging while underestimation may reflect greater risk for cognitive decline.

Biological heterogeneity in ADNI amnestic mild cognitive impairment

BackgroundPrevious work examining normal controls from the Alzheimer's Disease Neuroimaging Initiative (ADNI) identified substantial biological heterogeneity. We hypothesized that ADNI mild cognitive impairment (MCI) subjects would also exhibit heterogeneity with possible clinical implications. MethodsADNI subjects diagnosed with amnestic MCI (n = 138) were clustered based on baseline magnetic resonance imaging, cerebrospinal fluid, and serum biomarkers. The clusters were compared with respect to longitudinal atrophy, cognitive trajectory, and time to conversion. ResultsFour clusters emerged with distinct biomarker patterns: The first cluster was biologically similar to normal controls and rarely converted to Alzheimer's disease (AD) during follow-up. The second cluster had characteristics of early Alzheimer's pathology. The third cluster showed the most severe atrophy but barely abnormal tau levels and a substantial proportion converted to clinical AD. The fourth cluster appeared to be pre-AD and nearly all converted to AD. ConclusionsSubjects with MCI who were clinically similar showed substantial heterogeneity in biomarkers.

Biological heterogeneity in ADNI amnestic MCI

Background Previous work examining normal controls from the Alzheimer's Disease Neuroimaging Initiative (ADNI) identified substantial biological heterogeneity. We hypothesized that ADNI mild cognitive impairment (MCI) subjects would also exhibit heterogeneity with possible clinical implications.

For debate: substituting placebo controls in long-term Alzheimer's prevention trials

IntroductionNovel compounds with potential to attenuate or stop the progression of Alzheimer's disease (AD) from its presymptomatic stage to dementia are being tested in man. The study design commonly used is the long-term randomized, placebo-controlled trial (RPCT), meaning that many patients will receive placebo for 18 months or longer. It is ethically problematic to expose presymptomatic AD patients, who by definition are at risk of developing dementia, to prolonged placebo treatment. As an alternative to long-term RPCTs we propose a novel clinical study design, termed the placebo group simulation approach (PGSA), using mathematical models to forecast outcomes of presymptomatic AD patients from their own baseline data. Forecasted outcomes are compared with outcomes observed on candidate drugs, thus replacing a concomitant placebo group.MethodsFirst models were constructed using mild cognitive impairment (MCI) data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. One outcome is the Alzheimer Disease Assessment Scale - cognitive subscale (ADAScog) score after 24 months, predicted in a linear regression model; the other is the trajectory over 36 months of a composite neuropsychological test score (Neuro-Psychological Battery (NP-Batt)), using a mixed model. Demographics and clinical, biological and neuropsychological baseline values were tested as potential predictors in both models.ResultsADAScog scores after 24 months are predicted from gender, obesity, Functional Assessment Questionnaire (FAQ) and baseline scores of Mini-Mental State Examination, ADAScog and NP-Batt with an R2 of 0.63 and a residual standard deviation of 0.67, allowing reasonably precise estimates of sample means. The model of the NP-Batt trajectory has random intercepts and slopes and fixed effects for body mass index, time, apolipoprotein E4, age, FAQ, baseline scores of ADAScog and NP-Batt, and four interaction terms. Estimates of the residual standard deviation range from 0.3 to 0.5 on a standard normal scale. If novel drug candidates are expected to diminish the negative slope of scores with time, a change of 0.04 per year could be detected in samples of 400 with a power of about 80%.ConclusionsFirst PGSA models derived from ADNI MCI data allow prediction of cognitive endpoints and trajectories that correspond well with real observed values. Corroboration of these models with data from other observational studies is ongoing. It is suggested that the PGSA may complement RPCT designs in forthcoming long-term drug studies with presymptomatic AD individuals.

The ADNI multicenter study: CSF biomarkers data report

The goals of the Alzheimer's Disease Neuroimaging Initiative (ADNI) biochemical biomarker core include development of standardized biochemical biomarker methods for AD trials and validation of these methods by correlating them with imaging biomarker methods and neuropsychological and behavioral test data from the ADNI cohorts. Aβ1-42, total tau and tau phosphorylated at the threonine 181 position were measured in (a) CSF samples obtained during baseline evaluation of 100 mild AD, 196 mild cognitive impairment (MCI) and 114 elderly cognitively normal (NC) subjects participating in ADNI and in (b) an independent set of 56 autopsy-confirmed AD subjects and 52 age-matched elderly NC using a multicenter-qualified multiplex immunoassay system (Luminex platform and Innogenetics research reagents). Detection of an AD CSF profile for t-tau and Aβ1-42 levels in ADNI subjects was achieved using receiver operating characteristic (ROC) cutpoints and logistic regression models derived from the autopsy-confirmed CSF biomarker data. CSF Aβ1-42 was the most sensitive biomarker for AD detection in the autopsy-confirmed cohort of pathology-based CSF samples: ROC area under the curve of 0.913 and sensitivity for AD detection (96.4%), negative predictive value (95.2%), specificity for discriminating AD from elderly NC (76.9%), positive predictive value (81.8%) and overall test accuracy of 87%. In the ADNI cohort, a logistic regression model for Aβ1-42, t-tau and APOϵ4 allele count, provided the best assessment delineation of mild AD. An AD-like pathological baseline CSF profile for t-tau/Aβ1-42 was detected in 33/37 ADNI MCI subjects who converted to probable AD during the first year of the study. A unique characteristic for CSF Aβ1-42 concentrations was a bimodal distribution that was present in each of the three ADNI cohorts. The pathological CSF biomarker signature of AD defined by the combination of Aβ1-42 and t-tau in the autopsy-confirmed AD cohort and confirmed in the cohort followed in ADNI for 12 months provides effective delineation of mild AD detection in a large multisite prospective clinical investigation, and this signature appears to predict conversion from MCI to AD. This ongoing study is evaluating change with time of the concentrations of these biomarkers in CSF and assessments of relationships between the biochemical biomarkers and imaging biomarkers are underway.