Comparing neuropsychological, typical, and ADNI criteria for the diagnosis of mild cognitive impairment in Vietnam-era veterans.

OBJECTIVE: Neuropsychological criteria for mild cognitive impairment (MCI) more accurately predict progression to Alzheimer's disease (AD) and are more strongly associated with AD biomarkers and neuroimaging profiles than ADNI criteria. However, research to date has been conducted in relatively healthy samples with few comorbidities. Given that history of traumatic brain injury (TBI) and post-traumatic stress disorder (PTSD) are risk factors for AD and common in Veterans, we compared neuropsychological, typical (Petersen/Winblad), and ADNI criteria for MCI in Vietnam-era Veterans with histories of TBI or PTSD. METHOD: 267 Veterans (mean age = 69.8) from the DOD-ADNI study were evaluated for MCI using neuropsychological, typical, and ADNI criteria. Linear regressions adjusting for age and education assessed associations between MCI status and AD biomarker levels (cerebrospinal fluid [CSF] p-tau181, t-tau, and Aß42) by diagnostic criteria. Logistic regressions adjusting for age and education assessed the effects of TBI severity and PTSD symptom severity simultaneously on MCI classification by each criteria. RESULTS: Agreement between criteria was poor. Neuropsychological criteria identified more Veterans with MCI than typical or ADNI criteria, and were associated with higher CSF p-tau181 and t-tau. Typical and ADNI criteria were not associated with CSF biomarkers. PTSD symptom severity predicted MCI diagnosis by neuropsychological and ADNI criteria. History of moderate/severe TBI predicted MCI by typical and ADNI criteria. CONCLUSIONS: MCI diagnosis using sensitive neuropsychological criteria is more strongly associated with AD biomarkers than conventional diagnostic methods. MCI diagnostics in Veterans would benefit from incorporation of comprehensive neuropsychological methods and consideration of the impact of PTSD.

Data-driven classification of cognitively normal and mild cognitive impairment subtypes predicts progression in the NACC dataset.

INTRODUCTION: Data-driven neuropsychological methods can identify mild cognitive impairment (MCI) subtypes with stronger associations to dementia risk factors than conventional diagnostic methods. METHODS: Cluster analysis used neuropsychological data from participants without dementia (mean age = 71.6 years) in the National Alzheimer's Coordinating Center (NACC) Uniform Data Set (n = 26,255) and the "normal cognition" subsample (n = 16,005). Survival analyses examined MCI or dementia progression. RESULTS: Five clusters were identified: "Optimal" cognitively normal (oCN; 13.2%), "Typical" CN (tCN; 28.0%), Amnestic MCI (aMCI; 25.3%), Mixed MCI-Mild (mMCI-Mild; 20.4%), and Mixed MCI-Severe (mMCI-Severe; 13.0%). Progression to dementia differed across clusters (oCN < tCN < aMCI < mMCI-Mild < mMCI-Severe). Cluster analysis identified more MCI cases than consensus diagnosis. In the "normal cognition" subsample, five clusters emerged: High-All Domains (High-All; 16.7%), Low-Attention/Working Memory (Low-WM; 22.1%), Low-Memory (36.3%), Amnestic MCI (16.7%), and Non-amnestic MCI (naMCI; 8.3%), with differing progression rates (High-All < Low-WM = Low-Memory < aMCI < naMCI). DISCUSSION: Our data-driven methods outperformed consensus diagnosis by providing more precise information about progression risk and revealing heterogeneity in cognition and progression risk within the NACC "normal cognition" group.

Cognitive dispersion is elevated in amyloid-positive older adults and associated with regional hypoperfusion.

OBJECTIVE: Cognitive dispersion across neuropsychological measures within a single testing session is a promising marker predictive of cognitive decline and development of Alzheimer's disease (AD). However, little is known regarding brain changes underlying cognitive dispersion, and the association of cognitive dispersion with in vivo AD biomarkers and regional cerebral blood flow (CBF) has received limited study. We therefore examined associations among cognitive dispersion, amyloid-beta (Aß) positivity, and regional CBF among older adults free of dementia. METHOD: One hundred and forty-eight Alzheimer's Disease Neuroimaging Initiative (ADNI) participants underwent neuropsychological testing and neuroimaging. Pulsed arterial spin labeling (ASL) magnetic resonance imaging (MRI) was acquired to quantify CBF. Florbetapir positron emission tomography (PET) imaging determined Aß positivity. RESULTS: Adjusting for age, gender, education, and mean cognitive performance, older adults who were Aß+ showed higher cognitive dispersion relative to those who were Aß-. Across the entire sample, higher cognitive dispersion was associated with reduced CBF in inferior parietal and temporal regions. Secondary analyses stratified by Aß status demonstrated that higher cognitive dispersion was associated with reduced CBF among Aß+ individuals but not among those who were Aß-. CONCLUSIONS: Cognitive dispersion may be sensitive to early Aß accumulation and cerebrovascular changes adjusting for demographics and mean neuropsychological performance. Associations between cognitive dispersion and CBF were observed among Aß+ individuals, suggesting that cognitive dispersion may be a marker of brain changes among individuals on the AD continuum. Future studies should examine whether cognitive dispersion predicts brain changes in diverse samples and among those with greater vascular risk burden.

Regional White Matter Hyperintensities Relate to Specific Cognitive Abilities in Older Adults Without Dementia.

INTRODUCTION: White matter hyperintensities (WMHs) are magnetic resonance imaging markers of small vessel cerebrovascular disease that are associated with cognitive decline and clinical Alzheimer disease. Previous studies have often focused on global or total WMH; less is known about associations of regional WMHs and cognitive abilities among older adults without dementia. METHODS: A total of 610 older adults with normal cognition (n=302) or mild cognitive impairment (n=308) from the Alzheimer's Disease Neuroimaging Initiative underwent neuropsychological testing and magnetic resonance imaging. Linear regression models examined associations between regional WMH volumes and cognition, adjusting for age, sex, education, apolipoprotein E ε4 allele frequency, and pulse pressure. RESULTS: Among all participants, greater regional WMH volume in all lobes was associated with poorer performance on memory and speed/executive functioning. Among participants with normal cognition, greater temporal and occipital WMH volumes were associated with poorer memory, whereas no regional WMH volumes were associated with speed/executive function. DISCUSSION: Results show that greater regional WMH volume relates to poorer cognitive functioning-even among those with normal cognition. Together with results from previous studies, our findings raise the possibility that WMH may be a useful therapeutic target and/or important effect modifier in treatment or prevention dementia trials.

Diagnosing cognitive disorders in older adults with epilepsy.

OBJECTIVE: To characterize the nature and prevalence of cognitive disorders in older adults with temporal lobe epilepsy (TLE) and compare their cognitive profiles to patients with amnestic mild cognitive impairment (ie, aMCI). METHODS: Seventy-one older patients with TLE, 77 aMCI, and 69 normal aging controls (NACs), all 55-80 years of age, completed neuropsychological measures of memory, language, executive function, and processing speed. An actuarial neuropsychological method designed to diagnose MCI was applied to individual patients to identify older adults with TLE who met diagnostic criteria for MCI (TLE-MCI). A linear classifier was performed to evaluate how well the diagnostic criteria differentiated patients with TLE-MCI from aMCI. In TLE, the contribution of epilepsy-related and vascular risk factors to cognitive impairment was evaluated using multiple regression. RESULTS: Forty-three TLE patients (60%) met criteria for TLE-MCI, demonstrating marked deficits in both memory and language. When patients were analyzed according to age at seizure onset, 63% of those with an early onset (<50 years) versus 56% of those with late onset (≥ 50 years) met criteria for TLE-MCI. A classification model between TLE-MCI and aMCI correctly classified 81.1% (90.6% specificity, 61.3% sensitivity) of the cohort based on neuropsychological scores. Whereas TLE-MCI showed greater deficits in language relative to aMCI, patients with aMCI showed greater rapid forgetting on memory measures. Both epilepsy-related risk factors and the presence of leukoaraiosis on MRI contributed to impairment profiles in TLE-MCI. SIGNIFICANCE: Cognitive impairment is a common comorbidity in epilepsy and it presents in a substantial number of older adults with TLE. Although the underlying etiologies are unknown in many patients, the TLE-MCI phenotype may be secondary to an accumulation of epilepsy and vascular risk factors, signal the onset of a neurodegenerative disease, or represent a combination of factors.

Elevated plasma neurofilament light predicts a faster rate of cognitive decline over 5 years in participants with objectively-defined subtle cognitive decline and MCI.

INTRODUCTION: Neurofilament light (NFL) reflects neuroaxonal damage and is implicated in mild cognitive impairment (MCI) and Alzheimer's disease (AD). Little is known about NFL in pre-MCI stages, such as in individuals with objectively-defined subtle cognitive decline (Obj-SCD). METHODS: Two hundred ninety-four participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) underwent baseline blood draw and serial neuropsychological testing over 5 years of follow-up. RESULTS: Individuals with Obj-SCD and MCI showed elevated baseline plasma NFL relative to the cognitively normal (CN) group. Across the sample, elevated NFL predicted faster rate of cognitive and functional decline. Within the Obj-SCD and MCI groups, higher NFL levels predicted faster rate of decline in memory and preclinical AD composite score compared to the CN group. DISCUSSION: Findings demonstrate the utility of plasma NFL as a biomarker of early AD-related changes, and provide support for the use of Obj-SCD criteria in clinical research to better capture subtle cognitive changes.

Type 2 Diabetes Interacts With Alzheimer Disease Risk Factors to Predict Functional Decline.

OBJECTIVE: The current study examined the interactive effect of type 2 diabetes and Alzheimer disease (AD) risk factors on the rate of functional decline in cognitively normal participants from the Alzheimer's Disease Neuroimaging Initiative. METHODS: Participants underwent annual assessments that included the Functional Activities Questionnaire, an informant-rated measure of everyday functioning. Multilevel modeling, controlling for demographic variables and ischemic risk, examined the interactive effects of diabetes status (diabetes, n=69; no diabetes, n=744) and AD risk factors in the prediction of 5-year longitudinal change in everyday functioning. One model was run for each AD risk factor, including: objectively-defined subtle cognitive decline (Obj-SCD), and genetic susceptibility [apolipoprotein E ε4 (APOE ε4) as well as cerebrospinal fluid ß-amyloid (Aß), total tau (tau), and hyperphosphorylated tau (p-tau). RESULTS: The 3-way diabetes×AD risk factor×time interaction predicted increased rates of functional decline in models that examined Obj-SCD, APOE ε4, tau, and p-tau positivity, but not Aß positivity. CONCLUSIONS: Participants with both diabetes and at least 1 AD risk factor (ie, Obj-SCD, APOE ε4, tau, and p-tau positivity) demonstrated faster functional decline compared with those without both risk factors (diabetes or AD). These findings have implications for early identification of, and perhaps earlier intervention for, diabetic individuals at risk for future functional difficulty.

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

INTRODUCTION: The 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. METHODS: Three 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. RESULTS: There 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. CONCLUSIONS: Our 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.

MCI-to-normal reversion using neuropsychological criteria in the Alzheimer's Disease Neuroimaging Initiative.

INTRODUCTION: The low mild cognitive impairment (MCI) to cognitively normal (CN) reversion rate in the Alzheimer's Disease Neuroimaging Initiative (2-3%) suggests the need to examine reversion by other means. We applied comprehensive neuropsychological criteria (NP criteria) to determine the resulting MCI to CN reversion rate. METHODS: Participants with CN (n = 641) or MCI (n = 569) were classified at baseline and year 1 using NP criteria. Demographic, neuropsychological, and Alzheimer's disease biomarker variables as well as progression to dementia were examined across stable CN, reversion, and stable MCI groups. RESULTS: NP criteria produced a one-year reversion rate of 15.8%. Reverters had demographics, Alzheimer's disease biomarkers, and risk-of-progression most similar to the stable CN group and showed the most improvement on neuropsychological measures from baseline to year 1. DISCUSSION: NP criteria produced a reversion rate that is consistent with, albeit modestly improved from, reversion rates in meta-analyses. Reverters' biomarker profiles and progression rates suggest that NP criteria accurately tracked with underlying pathophysiologic status.

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

INTRODUCTION: We examined reasons for low mild cognitive impairment (MCI)-to-cognitively normal (CN) reversion rates in the Alzheimer's Disease Neuroimaging Initiative (ADNI). METHODS: CN 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. RESULTS: The 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. DISCUSSION: Results 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%.

Neuropsychological Criteria for Mild Cognitive Impairment in the Framingham Heart Study's Old-Old.

BACKGROUND/AIMS: Mild cognitive impairment (MCI) lacks a "gold standard" operational definition. The Jak/Bondi actuarial neuropsychological criteria for MCI are associated with improved diagnostic stability and prediction of progression to dementia compared to conventional MCI diagnostic approaches, although its utility in diagnosing MCI in old-old individuals (age 75+) is unknown. Therefore, we investigated the applicability of neuropsychological MCI criteria among old-old from the Framingham Heart Study. METHODS: A total of 347 adults (ages 79-102) were classified as cognitively normal or MCI via Jak/Bondi and conventional Petersen/Winblad criteria, which differ on cutoffs for cognitive impairment and number of impaired scores required for a diagnosis. Cox models examined MCI status in predicting risk of progression to dementia. RESULTS: MCI diagnosed by both the Jak/Bondi and Petersen/Winblad criteria was associated with incident dementia; however, when both criteria were included in the regression model together, only the Jak/Bondi criteria remained statistically significant. At follow-up, the Jak/Bondi criteria had a lower MCI-to-normal reversion rate than the Petersen/Winblad criteria. CONCLUSIONS: Our findings are consistent with previous research on the Jak/Bondi criteria and support the use of a comprehensive neuropsychological diagnostic approach for MCI among old-old individuals.

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).

Reflections on wisdom at the end of life: qualitative study of hospice patients aged 58-97 years.

ABSTRACTObjective:Wisdom is a complex trait, and previous research has identified several components of wisdom. This study explored the possible impact of a diagnosis of a terminal illness on the conceptualization and evolution of wisdom while facing the end of life. DESIGN AND PARTICIPANTS: Semi-structured qualitative interviews were conducted with 21 hospice patients aged 58-97 years who were in the last six months of their life. METHODS: Hospice patients were asked to describe the core characteristics of wisdom, as well as how their terminal illness might have impacted their understanding of this concept. The interviews were audiotaped, transcribed, and coded by the research team using a grounded theory analytic approach based on coding consensus, co-occurrence, and comparison. RESULTS: Broad concepts of wisdom described by the hospice patients align with the extant literature, thereby supporting those general conceptualizations. In addition, hospice patients described how their life perspectives shifted after being diagnosed with a terminal illness. Post-illness wisdom can be characterized as a dynamic balance of actively accepting the situation while simultaneously striving for galvanized growth. This delicate tension motivated the patients to live each day fully, yet consciously plan for their final legacy. CONCLUSION: The end of life offers a unique perspective on wisdom by highlighting the modulation between actively accepting the current situation while continuing the desire to grow and change at this critical time. This paradox, when embraced, may lead to even greater wisdom while facing one's own mortality.

Positive mental health in schizophrenia and healthy comparison groups: relationships with overall health and biomarkers.

OBJECTIVE: Positive psychological factors (PPFs) have been reported to have a significant impact on health in the general population. However, little is known about the relationship of these factors with mental and physical health in schizophrenia. METHOD: One hundred and thirty-five outpatients with schizophrenia and 127 healthy comparison subjects (HCs), aged 26-65 years, were evaluated with scales of resilience, optimism, happiness, and perceived stress. Measures of mental and physical health were also obtained. Regression analyses examined associations of a PPF composite with health variables. RESULTS: Relative to the HCs, the schizophrenia group had lower levels of PPFs. However, there was considerable heterogeneity, with over one-third of schizophrenia participants having values within the 'normative' range. The PPF composite was positively related to mental and physical health variables and with biomarkers of inflammation and insulin resistance. The relationship between PPFs and mental health was particularly strong for individuals with schizophrenia. CONCLUSION: A sizable minority of adults with chronic schizophrenia have levels of resilience, optimism, happiness, and perceived stress similar to HCs. Psychosocial interventions to enhance PPFs should be tested in patients with serious mental illnesses, with the goal of improving their mental health (beyond controlling symptoms of psychosis) and their physical health.

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).

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).

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).

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).

Susceptibility of the conventional criteria for mild cognitive impairment to false-positive diagnostic errors.

BACKGROUND: We assessed whether mild cognitive impairment (MCI) subtypes could be empirically derived within the Alzheimer's Disease Neuroimaging Initiative (ADNI) MCI cohort and examined associated biomarkers and clinical outcomes. METHODS: Cluster analysis was performed on neuropsychological data from 825 MCI ADNI participants. RESULTS: Four subtypes emerged: (1) dysnomic (n = 153), (2) dysexecutive (n = 102), (3) amnestic (n = 288), and (4) cluster-derived normal (n = 282) who performed within normal limits on cognitive testing. The cluster-derived normal group had significantly fewer APOE ε4 carriers and fewer who progressed to dementia compared with the other subtypes; they also evidenced cerebrospinal fluid Alzheimer's disease biomarker profiles that did not differ from the normative reference group. CONCLUSIONS: Identification of empirically derived MCI subtypes demonstrates heterogeneity in MCI cognitive profiles that is not captured by conventional criteria. The large cluster-derived normal group suggests that conventional diagnostic criteria are susceptible to false-positive errors, with the result that prior MCI studies may be diluting important biomarker relationships.

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.