Heterogeneous cortical atrophy patterns in MCI not captured by conventional diagnostic criteria

Brain imaging correlates of mild cognitive impairment and early dementia in patients with type 2 diabetes mellitus

BACKGROUND AND AIMS

The risk of mild cognitive impairment and dementia is increased in type 2 diabetes mellitus (T2DM). We aimed to identify the neuroanatomical correlates of mild cognitive impairment (MCI) and early dementia in patients with T2DM, using advanced multimodal MRI.

METHODS AND RESULTS

Twenty-five patients (≥70 years) with T2DM and MCI (n = 22) or early dementia (n = 3) were included. The reference group consisted of 23 patients with T2DM with intact cognition. All patients underwent a 3 T MRI. Brain volumes and white matter hyperintensity volumes were obtained with automated segmentation methods. White matter connectivity was assessed with diffusion tensor imaging and fiber tractography. Infarcts and microbleeds were rated visually. Compared to patients without cognitive impairment, those with impairment had a lower grey matter volume (effect size: -0.58, p=0.042), especially in the right temporal lobe and subcortical brain regions (effect sizes: -0.45 to -0.91, false discovery rate corrected p < 0.05). White matter volume (effect size: -0.47, p = 0.11) and white matter connectivity (effect size: 0.55, p = 0.054) were also reduced in patients with versus without cognitive impairment, albeit not statistically significant. White matter hyperintensity volumes and occurrence of other vascular lesions did not differ between the two patient groups.

CONCLUSION

In patients with T2DM, grey matter atrophy rather than vascular brain injury appears to be the primary imaging correlate of MCI and early dementia.

Understanding disease progression and improving Alzheimer's disease clinical trials: Recent highlights from the Alzheimer's Disease Neuroimaging Initiative

INTRODUCTION

The overall goal of the Alzheimer's Disease Neuroimaging Initiative (ADNI) is to validate biomarkers for Alzheimer's disease (AD) clinical trials. ADNI is a multisite, longitudinal, observational study that has collected many biomarkers since 2004. Recent publications highlight the multifactorial nature of late-onset AD. We discuss selected topics that provide insights into AD progression and outline how this knowledge may improve clinical trials.

METHODS

We used standard methods to identify nearly 600 publications using ADNI data from 2016 and 2017 (listed in Supplementary Material and searchable at http://adni.loni.usc.edu/news-publications/publications/).

RESULTS

(1) Data-driven AD progression models supported multifactorial interactions rather than a linear cascade of events. (2) β-Amyloid (Aβ) deposition occurred concurrently with functional connectivity changes within the default mode network in preclinical subjects and was followed by specific and progressive disconnection of functional and anatomical networks. (3) Changes in functional connectivity, volumetric measures, regional hypometabolism, and cognition were detectable at subthreshold levels of Aβ deposition. 4. Tau positron emission tomography imaging studies detailed a specific temporal and spatial pattern of tau pathology dependent on prior Aβ deposition, and related to subsequent cognitive decline. 5. Clustering studies using a wide range of modalities consistently identified a "typical AD" subgroup and a second subgroup characterized by executive impairment and widespread cortical atrophy in preclinical and prodromal subjects. 6. Vascular pathology burden may act through both Aβ dependent and independent mechanisms to exacerbate AD progression. 7. The APOE ε4 allele interacted with cerebrovascular disease to impede Aβ clearance mechanisms. 8. Genetic approaches identified novel genetic risk factors involving a wide range of processes, and demonstrated shared genetic risk for AD and vascular disorders, as well as the temporal and regional pathological associations of established AD risk alleles. 9. Knowledge of early pathological changes guided the development of novel prognostic biomarkers for preclinical subjects. 10. Placebo populations of randomized controlled clinical trials had highly variable trajectories of cognitive change, underscoring the importance of subject selection and monitoring. 11. Selection criteria based on Aβ positivity, hippocampal volume, baseline cognitive/functional measures, and APOE ε4 status in combination with improved cognitive outcome measures were projected to decrease clinical trial duration and cost. 12. Multiple concurrent therapies targeting vascular health and other AD pathology in addition to Aβ may be more effective than single therapies.

DISCUSSION

ADNI publications from 2016 and 2017 supported the idea of AD as a multifactorial disease and provided insights into the complexities of AD disease progression. These findings guided the development of novel biomarkers and suggested that subject selection on the basis of multiple factors may lower AD clinical trial costs and duration. The use of multiple concurrent therapies in these trials may prove more effective in reversing AD disease progression.

Increasing Inaccuracy of Self-Reported Subjective Cognitive Complaints Over 24 Months in Empirically Derived Subtypes of Mild Cognitive Impairment

OBJECTIVES

Although subjective cognitive complaints (SCC) are an integral component of the diagnostic criteria for mild cognitive impairment (MCI), previous findings indicate they may not accurately reflect cognitive ability. Within the Alzheimer's Disease Neuroimaging Initiative, we investigated longitudinal change in the discrepancy between self- and informant-reported SCC across empirically derived subtypes of MCI and normal control (NC) participants.

METHODS

Data were obtained for 353 MCI participants and 122 "robust" NC participants. Participants were classified into three subtypes at baseline via cluster analysis: amnestic MCI, mixed MCI, and cluster-derived normal (CDN), a presumptive false-positive group who performed within normal limits on neuropsychological testing. SCC at baseline and two annual follow-up visits were assessed via the Everyday Cognition Questionnaire (ECog), and discrepancy scores between self- and informant-report were calculated. Analysis of change was conducted using analysis of covariance.

RESULTS

The amnestic and mixed MCI subtypes demonstrated increasing ECog discrepancy scores over time. This was driven by an increase in informant-reported SCC, which corresponded to participants' objective cognitive decline, despite stable self-reported SCC. Increasing unawareness was associated with cerebrospinal fluid Alzheimer's disease biomarker positivity and progression to Alzheimer's disease. In contrast, CDN and NC groups over-reported cognitive difficulty and demonstrated normal cognition at all time points.

CONCLUSIONS

MCI participants' discrepancy scores indicate progressive underappreciation of their evolving cognitive deficits. Consistent over-reporting in the CDN and NC groups despite normal objective cognition suggests that self-reported SCC do not predict impending cognitive decline. Results demonstrate that self-reported SCC become increasingly misleading as objective cognitive impairment becomes more pronounced. (JINS, 2018, 24, 842-853).

Sex differences in the association between apolipoprotein E ε4 allele and Alzheimer's disease markers

Introduction

We determined whether the effect of apolipoprotein E (APOE)-ε4 genotype on Alzheimer's disease (AD) markers differs in men and women across AD stages.

Methods

Among normal control (NC) participants (N = 702) and participants with mild cognitive impairment (N = 576) and AD (N = 305), we examined the associations of sex and APOE-ε4 carrier status with cortical amyloid-β (Aβ) burden, hippocampal volume ratio (HpVR; hippocampal volume/intracranial volume × 10³), brain glucose metabolism, and verbal memory.

Results

In NC, APOE-ε4 related to greater Aβ burden and poorer verbal memory across sex but to smaller HpVR and hypometabolism in men only. In mild cognitive impairment, APOE-ε4 related to smaller HpVR, hypometabolism, greater Aβ burden, and poorer verbal memory across sex. In AD, APOE-ε4 related to greater Aβ burden in men only and smaller HpVR across sex and showed no association with hypometabolism or verbal memory.

Discussion

Sex differences in the association between APOE-ε4 and AD markers vary by disease stage.

Diagnostic and Prognostic Value of the Combination of Two Measures of Verbal Memory in Mild Cognitive Impairment due to Alzheimer's Disease

BACKGROUND

Episodic memory impairment is the core feature of typical Alzheimer's disease.

OBJECTIVE

To evaluate the performance of two commonly used verbal memory tests to detect mild cognitive impairment due to Alzheimer's disease (MCI-AD) and to predict progression to Alzheimer's disease dementia (AD-d).

METHODS

Prospective study of MCI patients in a tertiary memory disorder unit. Patients underwent an extensive neuropsychological battery including two tests of declarative verbal memory: The Free and Cued Selective Reminding Test (FCSRT) and the word list learning task from the Consortium to Establish a Registry for Alzheimer's disease (CERAD-WL). Cerebrospinal fluid (CSF) was obtained from all patients and MCI-AD was defined by means of the t-Tau/Aβ1-42 ratio. Logistic regression analyses tested whether the combination of FCSRT and CERAD-WL measures significantly improved the prediction of MCI-AD. Progression to AD-d was analyzed in a Cox regression model.

RESULTS

A total of 202 MCI patients with a mean follow-up of 34.2±24.2 months were included and 98 (48.5%) met the criteria for MCI-AD. The combination of FCSRT and CERAD-WL measures improved MCI-AD classification accuracy based on CSF biomarkers. Both tests yielded similar global predictive values (59.9-65.3% and 59.4-62.8% for FCSRT and CERAD-WL, respectively). MCI-AD patients with deficits in both FCSRT and CERAD-WL had a faster progression to AD-d than patients with deficits in only one test.

CONCLUSIONS

The combination of FCSRT and CERAD-WL improves the classification of MCI-AD and defines different prognostic profiles. These findings have important implications for clinical practice and the design of clinical trials.

Word-list intrusion errors predict progression to mild cognitive impairment

OBJECTIVE

Preclinical Alzheimer's disease (AD) defined by a positive AD biomarker in the presence of normal cognition is presumed to precede mild cognitive impairment (MCI). Subtle cognitive deficits and cognitive inefficiencies in preclinical AD may be detected through process and error scores on neuropsychological tests in those at risk for progression to MCI.

METHOD

Cognitively normal participants (n = 525) from the Alzheimer's Disease Neuroimaging Initiative were followed for up to 5 years and classified as either stable normal (n = 305) or progressed to MCI (n = 220). Cox regressions were used to determine whether baseline process scores on the Rey Auditory Verbal Learning Test (AVLT; intrusion errors, learning slope, proactive interference, retroactive interference) predicted progression to MCI and a Clinical Dementia Rating (CDR) score of 1 after considering demographic characteristics, apolipoprotein E ε4 status, cerebrospinal fluid AD biomarkers, ischemia risk, mood, functional difficulty, and standard neuropsychological total test scores for the model.

RESULTS

Baseline AVLT intrusion errors predicted progression to MCI (hazard ratio = 1.04, 95% confidence interval 1.01-1.07, p = .008) and improved model fit after the other valuable predictors were already in the model, χ2(df = 1) = 6.330, p = .012. AVLT intrusion errors also predicted progression to CDR = 1 (hazard ratio = 1.10, 95% confidence interval 1.02-1.18, p = .016) and again improved model fit, χ2(df = 1) = 4.682, p = .030.

CONCLUSIONS

Intrusion errors on the AVLT contribute unique value for predicting progression from normal cognition to MCI and normal cognition to mild dementia (CDR = 1). Intrusion errors appear to reflect subtle change and inefficiencies in cognition that precede impairment detected by neuropsychological total scores. (PsycINFO Database Record

Unmasking the benefits of donepezil via psychometrically precise identification of mild cognitive impairment: A secondary analysis of the ADCS vitamin E and donepezil in MCI study

Introduction

Criteria for mild cognitive impairment (MCI) used in many clinical trials are susceptible to "false-positive (FP)" errors that can be avoided by an actuarial psychometric approach.

Methods

Cluster analysis was applied to baseline neuropsychological test data from 756 MCI participants in the Alzheimer's Disease Cooperative Study donepezil trial. Treatment groups were compared after FP MCI cases were removed.

Results

Cluster analyses revealed three groups: "single-domain amnestic MCI" (31%), "multi-domain amnestic MCI" (39%), and "FP MCI" (30%). After removing FP MCI cases, the donepezil treatment group had a lower rate of progression to Alzheimer's disease and better performance on cognitive tests than the placebo/vitamin E group.

Discussion

Removal of FP MCI diagnoses unmasked beneficial effects of donepezil, despite a 30% reduction in sample size. MCI subject selection based on actuarial methods with comprehensive neuropsychological test data can result in more efficient clinical trials and improved ability to detect treatment effects.

Alzheimer's Disease: Past, Present, and Future

Although dementia has been described in ancient texts over many centuries (e.g., "Be kind to your father, even if his mind fail him." - Old Testament: Sirach 3:12), our knowledge of its underlying causes is little more than a century old. Alzheimer published his now famous case study only 110 years ago, and our modern understanding of the disease that bears his name, and its neuropsychological consequences, really only began to accelerate in the 1980s. Since then we have witnessed an explosion of basic and translational research into the causes, characterizations, and possible treatments for Alzheimer's disease (AD) and other dementias. We review this lineage of work beginning with Alzheimer's own writings and drawings, then jump to the modern era beginning in the 1970s and early 1980s and provide a sampling of neuropsychological and other contextual work from each ensuing decade. During the 1980s our field began its foundational studies of profiling the neuropsychological deficits associated with AD and its differentiation from other dementias (e.g., cortical vs. subcortical dementias). The 1990s continued these efforts and began to identify the specific cognitive mechanisms affected by various neuropathologic substrates. The 2000s ushered in a focus on the study of prodromal stages of neurodegenerative disease before the full-blown dementia syndrome (i.e., mild cognitive impairment). The current decade has seen the rise of imaging and other biomarkers to characterize preclinical disease before the development of significant cognitive decline. Finally, we suggest future directions and predictions for dementia-related research and potential therapeutic interventions. (JINS, 2017, 23, 818-831).

Statistically Derived Subtypes and Associations with Cerebrospinal Fluid and Genetic Biomarkers in Mild Cognitive Impairment: A Latent Profile Analysis

OBJECTIVES

Research demonstrates heterogeneous neuropsychological profiles among individuals with mild cognitive impairment (MCI). However, few studies have included visuoconstructional ability or used latent mixture modeling to statistically identify MCI subtypes. Therefore, we examined whether unique neuropsychological MCI profiles could be ascertained using latent profile analysis (LPA), and subsequently investigated cerebrospinal fluid (CSF) biomarkers, genotype, and longitudinal clinical outcomes between the empirically derived classes.

METHODS

A total of 806 participants diagnosed by means of the Alzheimer's Disease Neuroimaging Initiative (ADNI) MCI criteria received a comprehensive neuropsychological battery assessing visuoconstructional ability, language, attention/executive function, and episodic memory. Test scores were adjusted for demographic characteristics using standardized regression coefficients based on "robust" normal control performance (n=260). Calculated Z-scores were subsequently used in the LPA, and CSF-derived biomarkers, genotype, and longitudinal clinical outcome were evaluated between the LPA-derived MCI classes.

RESULTS

Statistical fit indices suggested a 3-class model was the optimal LPA solution. The three-class LPA consisted of a mixed impairment MCI class (n=106), an amnestic MCI class (n=455), and an LPA-derived normal class (n=245). Additionally, the amnestic and mixed classes were more likely to be apolipoprotein e4+ and have worse Alzheimer's disease CSF biomarkers than LPA-derived normal subjects.

CONCLUSIONS

Our study supports significant heterogeneity in MCI neuropsychological profiles using LPA and extends prior work (Edmonds et al., 2015) by demonstrating a lower rate of progression in the approximately one-third of ADNI MCI individuals who may represent "false-positive" diagnoses. Our results underscore the importance of using sensitive, actuarial methods for diagnosing MCI, as current diagnostic methods may be over-inclusive. (JINS, 2017, 23, 564-576).

Longitudinal Trajectories of Informant-Reported Daily Functioning in Empirically Defined Subtypes of Mild Cognitive Impairment

OBJECTIVES

Within the Alzheimer's Disease Neuroimaging Initiative (ADNI)'s mild cognitive impairment (MCI) cohort, we previously identified MCI subtypes as well as participants initially diagnosed with MCI but found to have normal neuropsychological, biomarker, and neuroimaging profiles. We investigated the functional change over time in these empirically derived MCI subgroups.

METHODS

ADNI MCI participants (n=654) were classified using cluster analysis as Amnestic MCI (single-domain memory impairment), Dysnomic MCI (memory+language impairments), Dysexecutive/Mixed MCI (memory+language+attention/executive impairments), or Cluster-Derived Normal (CDN). Robust normal control participants (NCs; n=284) were also examined. The Functional Activities Questionnaire (FAQ) was administered at baseline through 48-month follow-up. Multilevel modeling examined FAQ trajectories by cognitive subgroup.

RESULTS

The Dysexecutive/Mixed group demonstrated the fastest rate of decline across all groups. Amnestic and Dysnomic groups showed steeper rates of decline than CDNs. While CDNs had more functional difficulty than NCs across visits, both groups' mean FAQ scores remained below its suggested cutoff at all visits.

CONCLUSIONS

Results (a) show the importance of executive dysfunction in the context of other impaired cognitive domains when predicting functional decline in at-risk elders, and (b) support our previous work demonstrating that ADNI's MCI criteria may have resulted in false-positive MCI diagnoses, given the CDN's better FAQ trajectory than those of the cognitively impaired MCI groups. (JINS, 2017, 23, 521-527).

Patterns of Cortical and Subcortical Amyloid Burden across Stages of Preclinical Alzheimer's Disease

OBJECTIVES

We examined florbetapir positron emission tomography (PET) amyloid scans across stages of preclinical Alzheimer's disease (AD) in cortical, allocortical, and subcortical regions. Stages were characterized using empirically defined methods.

METHODS

A total of 312 cognitively normal Alzheimer's Disease Neuroimaging Initiative participants completed a neuropsychological assessment and florbetapir PET scan. Participants were classified into stages of preclinical AD using (1) a novel approach based on the number of abnormal biomarkers/cognitive markers each individual possessed, and (2) National Institute on Aging and the Alzheimer's Association (NIA-AA) criteria. Preclinical AD groups were compared to one another and to a mild cognitive impairment (MCI) sample on florbetapir standardized uptake value ratios (SUVRs) in cortical and allocortical/subcortical regions of interest (ROIs).

RESULTS

Amyloid deposition increased across stages of preclinical AD in all cortical ROIs, with SUVRs in the later stages reaching levels seen in MCI. Several subcortical areas showed a pattern of results similar to the cortical regions; however, SUVRs in the hippocampus, pallidum, and thalamus largely did not differ across stages of preclinical AD.

CONCLUSIONS

Substantial amyloid accumulation in cortical areas has already occurred before one meets criteria for a clinical diagnosis. Potential explanations for the unexpected pattern of results in some allocortical/subcortical ROIs include lack of correspondence between (1) cerebrospinal fluid and florbetapir PET measures of amyloid, or between (2) subcortical florbetapir PET SUVRs and underlying neuropathology. Findings support the utility of our novel method for staging preclinical AD. By combining imaging biomarkers with detailed cognitive assessment to better characterize preclinical AD, we can advance our understanding of who is at risk for future progression. (JINS, 2016, 22, 978-990).