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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 -tau 181 , t -tau, and A β 42 ) 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 -tau 181 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.

Objective: We examined whether intraindividual variability (IIV) across tests of executive functions (EF-IIV) is elevated in Veterans with a history of mild traumatic brain injury (mTBI) relative to military controls (MCs) without a history of mTBI. We also explored relationships among EF-IIV, white matter microstructure, and posttraumatic stress disorder (PTSD) symptoms., Method: A total of 77 Veterans (mTBI = 43, MCs = 34) completed neuropsychological testing, diffusion tensor imaging (DTI), and PTSD symptom ratings. EF-IIV was calculated as the standard deviation across six tests of EF, along with an EF-Mean composite. DSI Studio connectometry analysis identified white matter tracts significantly associated with EF-IIV according to generalized fractional anisotropy (GFA)., Results: After adjusting for EF-Mean and PTSD symptoms, the mTBI group showed significantly higher EF-IIV than MCs. Groups did not differ on EF-Mean after adjusting for PTSD symptoms. Across groups, PTSD symptoms significantly negatively correlated with EF-Mean, but not with EF-IIV. EF-IIV significantly negatively correlated with GFA in multiple white matter pathways connecting frontal and more posterior regions., Conclusions: Veterans with mTBI demonstrated significantly greater IIV across EF tests compared to MCs, even after adjusting for mean group differences on those measures as well as PTSD severity. Findings suggest that, in contrast to analyses that explore effects of mean performance across tests, discrepancy analyses may capture unique variance in neuropsychological performance and more sensitively capture cognitive disruption in Veterans with mTBI histories. Importantly, findings show that EF-IIV is negatively associated with the microstructure of white matter pathways interconnecting cortical regions that mediate executive function and attentional processes.

Objectives: Research has shown that analyzing intrusion errors generated on verbal learning and memory measures is helpful for distinguishing between the memory disorders associated with Alzheimer's disease (AD) and other neurological disorders, including Huntington's disease (HD). Moreover, preliminary evidence suggests that certain clinical populations may be prone to exhibit different types of intrusion errors., Methods: We examined the prevalence of two new California Verbal Learning Test-3 (CVLT-3) intrusion subtypes - across-trial novel intrusions and across/within trial repeated intrusions - in individuals with AD or HD. We hypothesized that the encoding/storage impairment associated with medial-temporal involvement in AD would result in a greater number of novel intrusions on the delayed recall trials of the CVLT-3, whereas the executive dysfunction associated with subcortical-frontal involvement in HD would result in a greater number of repeated intrusions across trials., Results: The AD group generated significantly more across-trial novel intrusions than across/within trial repeated intrusions on the delayed cued-recall trials, whereas the HD group showed the opposite pattern on the delayed free-recall trials., Conclusions: These new intrusion subtypes, combined with traditional memory analyses (e.g., recall versus recognition performance), promise to enhance our ability to distinguish between the memory disorders associated with primarily medial-temporal versus subcortical-frontal involvement.

Objectives: The third edition of the California Verbal Learning Test (CVLT-3) includes a new index termed List A versus Novel/Unrelated recognition discriminability (RD) on the Yes/No Recognition trial. Whereas the Total RD index incorporates false positive (FP) errors associated with all distractors (including List B and semantically related items), the new List A versus Novel/Unrelated RD index incorporates only FP errors associated with novel, semantically unrelated distractors. Thus, in minimizing levels of source and semantic interference, the List A versus Novel/Unrelated RD index may yield purer assessments of yes/no recognition memory independent of vulnerability to source memory difficulties or semantic confusion, both of which are often seen in individuals with primarily frontal-system dysfunction (e.g., early Huntington's disease [HD])., Methods: We compared the performance of individuals with Alzheimer's disease (AD) and HD in mild and moderate stages of dementia on CVLT-3 indices of Total RD and List A versus Novel/Unrelated RD., Results: Although AD and HD subgroups exhibited deficits on both RD indices relative to healthy comparison groups, those with HD generally outperformed those with AD, and group differences were more robust on List A versus Novel/Unrelated RD than on Total RD., Conclusions: Our findings highlight the clinical utility of the new CVLT-3 List A versus Novel/Unrelated RD index, which (a) maximally assesses yes/no recognition memory independent of source and semantic interference; and (b) provides a greater differentiation between individuals whose memory disorder is primarily at the encoding/storage level (e.g., as in AD) versus at the retrieval level (e.g., as in early HD). (JINS, 2018, 24, 833-841).

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).

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).

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).

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).

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.

Given the importance of identifying dementia prodromes for future treatment efforts, we examined two methods of diagnosing mild cognitive impairment (MCI) and determined whether empirically-derived MCI subtypes of these diagnostic methods were consistent with one another as well as with conventional MCI subtypes (i.e., amnestic, non-amnestic, single-domain, multi-domain). Participants were diagnosed with MCI using either conventional Petersen/Winblad criteria (n = 134; >1.5 SDs below normal on one test within a cognitive domain) or comprehensive neuropsychological criteria developed by Jak et al. (2009) (n = 80; >1 SD below normal on two tests within a domain), and the resulting samples were examined via hierarchical cluster and discriminant function analyses. Results showed that neuropsychological profiles varied depending on the criteria used to define MCI. Both criteria revealed an Amnestic subtype, consistent with prodromal Alzheimer's disease (AD), and a Mixed subtype that may capture individuals in advanced stages of MCI. The comprehensive criteria uniquely yielded Dysexecutive and Visuospatial subtypes, whereas the conventional criteria produced a subtype that performed within normal limits, suggesting its susceptibility to false positive diagnostic errors. Whether these empirically-derived MCI subtypes correspond to dissociable neuropathologic substrates and represent reliable prodromes of dementia will require additional follow-up.

Libon et al. (2010) provided evidence for three statistically determined clusters of patients with mild cognitive impairment (MCI): amnesic (aMCI), dysexecutive (dMCI), and mixed (mxMCI). The current study further examined dysexecutive impairment in MCI using the framework of Fuster's (1997) derailed temporal gradients, that is, declining performance on executive tests over time or test epoch. Temporal gradients were operationally defined by calculating the slope of aggregate letter fluency output across 15-s epochs and accuracy indices for initial, middle, and latter triads from the Wechsler Memory Scale-Mental Control subtest (Boston Revision). For letter fluency, slope was steeper for dMCI compared to aMCI and NC groups. Between-group Mental Control analyses for triad 1 revealed worse dMCI performance than NC participants. On triad 2, dMCI scored lower than aMCI and NCs; on triad 3, mxMCI performed worse versus NCs. Within-group Mental Control analyses yielded equal performance across all triads for aMCI and NC participants. mxMCI scored lower on triad 1 compared to triads 2 and 3. dMCI participants also performed worse on triad 1 compared to triads 2 and 3, but scored higher on triad 3 versus triad 2. These data suggest impaired temporal gradients may provide a useful heuristic for understanding dysexecutive impairment in MCI.

Using cluster analysis Libon et al. (2010) found three verbal serial list-learning profiles involving delay memory test performance in patients with mild cognitive impairment (MCI). Amnesic MCI (aMCI) patients presented with low scores on delay free recall and recognition tests; mixed MCI (mxMCI) patients scored higher on recognition compared to delay free recall tests; and dysexecutive MCI (dMCI) patients generated relatively intact scores on both delay test conditions. The aim of the current research was to further characterize memory impairment in MCI by examining forgetting/savings, interference from a competing word list, intrusion errors/perseverations, intrusion word frequency, and recognition foils in these three statistically determined MCI groups compared to normal control (NC) participants. The aMCI patients exhibited little savings, generated more highly prototypic intrusion errors, and displayed indiscriminate responding to delayed recognition foils. The mxMCI patients exhibited higher saving scores, fewer and less prototypic intrusion errors, and selectively endorsed recognition foils from the interference list. dMCI patients also selectively endorsed recognition foils from the interference list but performed similarly compared to NC participants. These data suggest the existence of distinct memory impairments in MCI and caution against the routine use of a single memory test score to operationally define MCI.

There is increasing consensus regarding the importance of operationally defining and measuring functional decline in mild cognitive impairment (MCI). However, few studies have directly examined functional abilities in MCI or its presumed subtypes and, to date, reported findings have been discrepant. Nondemented older adults (n = 120) were administered a comprehensive cognitive battery measuring multiple domains as well as a performance-based functional ability measure. Participants were characterized as either cognitively normal, amnestic MCI, or non-amnestic MCI. MCI individuals demonstrated decrements in instrumental activities of daily living (IADL) relative to their cognitively normal counterparts. Specifically, participants with amnestic MCI demonstrated significant decrements in financial management, whereas those with non-amnestic MCI showed poorer performance in abilities related to health and safety. Moreover, decreased functional abilities were associated with decrements in global cognitive functioning but not memory or executive functions in the MCI participants. Finally, logistic regression demonstrated that functional abilities accurately predicted MCI subtype. Results support the need for better delineation of functional decline in MCI. Given the implications of functional status for MCI diagnosis and treatment, the direct assessment of functional abilities is recommended. Results further suggest performance-based IADL assessment may have utility in distinguishing MCI subtypes.

Wide-ranging conceptual and diagnostic approaches to defining mild cognitive impairment (MCI) have led to highly variable prevalence and progression rates. We sought to examine whether bilateral hippocampal volumes and cerebrovascular risk factors in individuals characterized by two different neuropsychological definitions of MCI subtypes would also differ. Participants were 65 nondemented, community-dwelling, older adults, ages 62-91 years, drawn from a larger group of individuals enrolled in a longitudinal study of normal aging. A comprehensive neuropsychological definition of MCI that required the presence of more than one impaired score in a cognitive domain resulted in expected anatomical results; hippocampal volumes were significantly smaller in the aMCI group as compared to cognitively normal or nonamnestic MCI participants. However, a typical definitional scheme for classifying MCI based only on the presence of one impaired score within a cognitive domain did not result in hippocampal differences between groups. Global stroke risk factors did not differ between the two definitional schemes, although the relationship between stroke risk variables and neuropsychological performance did vary by diagnostic approach. The comprehensive approach demonstrated associations between stroke risk and cognition, whereas the typical approach did not. Use of more sophisticated clinical decision-making and diagnostic approaches that incorporate comprehensive neuropsychological assessment techniques is supported by this convergence of neuropsychological, neuropathological, and stroke risk findings.

This study examined whether distinct neuropsychological profiles could be delineated in a sample with Mild Cognitive Impairment (MCI) and whether white matter lesion (WML) burden contributed to MCI group differences. A heterogeneous, clinical sample of 70 older adults diagnosed with MCI was assessed using cognitive scores, and WML was quantified using a semi-automated, volumetric approach on T2-weighted fluid-attenuated inversion recovery (FLAIR) images. Using cluster and discriminant analyses, three distinct groups (Memory/Language, Executive/Processing Speed, and Pure Memory) were empirically derived based on cognitive scores. Results also showed a dose dependent relationship of WML burden to MCI subgroup, with the Executive/Processing Speed subgroup demonstrating significantly higher levels of WML pathology when compared to the other subgroups. In addition, there was a dissociation of lesion type by the two most impaired subgroups (Memory/Language and Executive/Processing Speed) such that the Memory/Language subgroup showed higher periventricular lesion (PVL) and lower deep white matter lesion (DWML) volumes, whereas the Executive/Processing Speed demonstrated higher DWML and lower PVL volumes. Results demonstrate that distinct MCI subgroups can be empirically derived and reliably differentiated from a heterogeneous MCI sample, and that these profiles differ according to WML burden. Overall, findings suggest different underlying pathologies within MCI and contribute to our understanding of MCI subtypes.