The heterogeneity of mild cognitive impairment: a neuropsychological analysis

Multimodal analysis of disease onset in Alzheimer's disease using Connectome, Molecular, and genetics data

Alzheimer's disease (AD) and its related age at onset (AAO) are highly heterogeneous, due to the inherent complexity of the disease. They are affected by multiple factors, such as neuroimaging and genetic predisposition. Multimodal integration of various data types is necessary; however, it has been nontrivial due to the high dimensionality of each modality. We aimed to identify multimodal biomarkers of AAO in AD using an extended version of sparse canonical correlation analysis, in which we integrated two imaging modalities, functional magnetic resonance imaging (fMRI) and positron emission tomography (PET), and genetic data in the form of single-nucleotide polymorphisms (SNPs) obtained from the Alzheimer's disease neuroimaging initiative database. These three modalities cover low-to-high-level complementary information and offer multiscale insights into the AAO. We identified multivariate markers of AAO in AD using fMRI, PET, and SNP. Furthermore, the markers identified were largely consistent with those reported in the existing literature. In particular, our serial mediation analysis suggests that genetic variants influence the AAO in AD by indirectly affecting brain connectivity by mediation of amyloid-beta protein accumulation, supporting a plausible path in existing research. Our approach provides comprehensive biomarkers related to AAO in AD and offers novel multimodal insights into AD.

The role of cognitive flexibility on higher level executive functions in mild cognitive impairment and healthy older adults

BACKGROUND

Mild Cognitive Impairment (MCI) is a preclinical condition between healthy and pathological aging, which is characterized by impairments in executive functions (EFs), including cognitive flexibility. According to Diamond's model, cognitive flexibility is a core executive function, along with working memory and inhibition, but it requires the development of these last EFs to reach its full potential. In this model, planning and fluid intelligence are considered higher-level EFs. Given their central role in enabling individuals to adapt their daily life behavior efficiently, the goal is to gain valuable insight into the functionality of cognitive flexibility in a preclinical form of cognitive decline. This study aims to investigate the role of cognitive flexibility and its components, set-shifting and switching, in MCI. The hypotheses are as follows: (I) healthy participants are expected to perform better than those with MCI on cognitive flexibility and higher-level EFs tasks, taking into account the mediating role of global cognitive functioning; (II) cognitive flexibility can predict performance on higher-level EFs (i.e., planning and fluid intelligence) tasks differently in healthy individuals and those diagnosed with MCI.

METHODS

Ninety participants were selected and divided into a healthy control group (N = 45; mean age 64.1 ± 6.80; 66.6% female) and an MCI group (N = 45; mean age 65.2 ± 8.14; 40% female). Cognitive flexibility, fluid intelligence, planning, and global cognitive functioning of all participants were assessed using standardized tasks.

RESULTS

Results indicated that individuals with MCI showed greater impairment in global cognitive functioning and EFs performance. Furthermore, the study confirms the predictive role of cognitive flexibility for higher EFs in individuals with MCI and only partially in healthy older adults.

Characterizing cognitive profiles in diverse middle-aged and older Hispanics/Latinos: Study of Latinos-Investigation of Neurocognitive Aging (HCHS/SOL)

Introduction

We investigated cognitive profiles among diverse, middle-aged and older Hispanic/Latino adults in the Study of Latinos-Investigation of Neurocognitive Aging (SOL-INCA) cohort using a cross-sectional observational study design.

Methods

Based on weighted descriptive statistics, the average baseline age of the target population was 56.4 years, slightly more than half were women (54.6%), and 38.4% reported less than a high school education. We used latent profile analysis of demographically adjusted z scores on SOL-INCA neurocognitive tests spanning domains of verbal memory, language, processing speed, and executive function.

Results

Statistical fit assessment indices combined with clinical interpretation suggested five profiles: (1) a Higher Global group performing in the average-to-high-average range across all cognitive and instrumental activity of daily living (IADL) tests (13.8%); (2) a Higher Memory group with relatively high performance on memory tests but average performance across all other cognitive/IADL tests (24.6%); (3) a Lower Memory group with relatively low performance on memory tests but average performance across all other cognitive/IADL tests (32.8%); (4) a Lower Executive Function group with relatively low performance on executive function and processing speed tests but average-to-low-average performance across all other cognitive/IADL tests (16.6%); and (5) a Lower Global group performing low-average-to-mildly impaired across all cognitive/IADL tests (12.1%).

Discussion

Our results provide evidence of heterogeneity in the cognitive profiles of a representative, community-dwelling sample of diverse Hispanic/Latino adults. Our analyses yielded cognitive profiles that may assist efforts to better understand the early cognitive changes that may portend Alzheimer's disease and related dementias among diverse Hispanics/Latinos.

Highlights

The present study characterized cognitive profiles among diverse middle-aged and older Hispanic/Latino adults.Latent profile analysis of neurocognitive test scores was the primary analysis conducted.The target population consists of middle-aged and older Hispanic/Latino adults enrolled in the Hispanic Community Health Study/Study of Latinos and ancillary Study of Latinos - Investigation of Neurocognitive Aging.

Heterogeneity in subjective cognitive decline in the Sino Longitudinal Study on Cognitive Decline(SILCODE): Empirically derived subtypes, structural and functional verification

AIMS

We evaluated whether Subjective Cognitive Decline (SCD) subtypes could be empirically derived within the Sino Longitudinal Study on Cognitive Decline (SILCODE) SCD cohort and examined associated neuroimaging markers, biomarkers, and clinical outcomes.

METHODS

A cluster analysis was performed on eight neuropsychological test scores from 124 SCD SILCODE participants and 57 normal control (NC) subjects. Structural and functional neuroimaging indices were used to evaluate the SCD subgroups.

RESULTS

Four subtypes emerged: (1) dysexecutive/mixed SCD (n = 23), (2) neuropsychiatric SCD (n = 24), (3) amnestic SCD (n = 22), and (4) cluster-derived normal (n = 55) who exhibited normal performance in neuropsychological tests. Compared with the NC group, each subgroup showed distinct patterns in gray matter (GM) volume and the amplitude of low-frequency fluctuations (ALFF). Lower fractional anisotropy (FA) values were only found in the neuropsychiatric SCD group relative to NC.

CONCLUSION

The identification of empirically derived SCD subtypes demonstrates the presence of heterogeneity in SCD neuropsychological profiles. The cluster-derived normal group may represent the majority of SCD individuals who do not show progressive cognitive decline; the dysexecutive/mixed SCD and amnestic SCD might represent high-risk groups with progressing cognitive decline; and finally, the neuropsychiatric SCD may represent a new topic in SCD research.

Memory Binding Test and Its Associations With Hippocampal Volume Across the Cognitive Continuum Preceding Dementia

Innovative memory paradigms have been introduced to capture subtle memory changes in early Alzheimer's disease (AD). We aimed to examine the associations between different indexes of the challenging Memory Binding Test (MBT) and hippocampal volume (HV) in a sample of individuals with subjective cognitive decline (SCD; n = 50), amnestic mild cognitive impairment (aMCI) due to AD (n = 31), and cognitively normal (CN) older adults (n = 29) recruited from the Czech Brain Aging Study, in contrast to traditional verbal memory tests. Both MBT free and cued recall scores in immediate and delayed recall conditions were associated with lower HV in both SCD and aMCI due to AD, whereas in traditional verbal memory tests only delayed recall scores were associated with lower HV. In SCD, the associations with lower HV in the immediate recall covered specific cued recall indexes only. In conclusion, the MBT is a promising test for detecting subtle hippocampal-associated memory decline during the predementia continuum.

Comorbidity-driven multi-modal subtype analysis in mild cognitive impairment of Alzheimer's disease

BACKGROUND

Mild cognitive impairment (MCI) is a heterogeneous condition with high individual variabilities in clinical outcomes driven by patient demographics, genetics, brain structure features, blood biomarkers, and comorbidities. Multi-modality data-driven approaches have been used to discover MCI subtypes; however, disease comorbidities have not been included as a modality though multiple diseases including hypertension are well-known risk factors for Alzheimer's disease (AD). The aim of this study was to examine MCI heterogeneity in the context of AD-related comorbidities along with other AD-relevant features and biomarkers.

METHODS

A total of 325 MCI subjects with 32 AD-relevant comorbidities and features were considered. Mixed-data clustering is applied to discover and compare MCI subtypes with and without including AD-related comorbidities. Finally, the relevance of each comorbidity-driven subtype was determined by examining their MCI to AD disease prognosis, descriptive statistics, and conversion rates.

RESULTS

We identified four (five) MCI subtypes: poor-, average-, good-, and best-AD prognosis by including comorbidities (without including comorbidities). We demonstrated that comorbidity-driven MCI subtypes differed from those identified without comorbidity information. We further demonstrated the clinical relevance of comorbidity-driven MCI subtypes. Among the four comorbidity-driven MCI subtypes there were substantial differences in the proportions of participants who reverted to normal function, remained stable, or converted to AD. The groups showed different behaviors, having significantly different MCI to AD prognosis, significantly different means for cognitive test-related and plasma features, and by the proportion of comorbidities.

CONCLUSIONS

Our study indicates that AD comorbidities should be considered along with other diverse AD-relevant characteristics to better understand MCI heterogeneity.

Uncovering heterogeneous cognitive trajectories in mild cognitive impairment: a data-driven approach

BACKGROUND

Given the complex and progressive nature of mild cognitive impairment (MCI), the ability to delineate and understand the heterogeneous cognitive trajectories is crucial for developing personalized medicine and informing trial design. The primary goals of this study were to examine whether different cognitive trajectories can be identified within subjects with MCI and, if present, to characterize each trajectory in relation to changes in all major Alzheimer's disease (AD) biomarkers over time.

METHODS

Individuals with a diagnosis of MCI at the first visit and ≥ 1 follow-up cognitive assessment were selected from the Alzheimer's Disease Neuroimaging Initiative database (n = 936; age 73 ± 8; 40% female; 16 ± 3 years of education; 50% APOE4 carriers). Based on the Alzheimer's Disease Assessment Scale-Cognitive Subscale-13 (ADAS-Cog-13) total scores from baseline up to 5 years follow-up, a non-parametric k-means longitudinal clustering method was performed to obtain clusters of individuals with similar patterns of cognitive decline. We further conducted a series of linear mixed-effects models to study the associations of cluster membership with longitudinal changes in other cognitive measures, neurodegeneration, and in vivo AD pathologies.

RESULTS

Four distinct cognitive trajectories emerged. Cluster 1 consisted of 255 individuals (27%) with a nearly non-existent rate of change in the ADAS-Cog-13 over 5 years of follow-up and a healthy-looking biomarker profile. Individuals in the cluster 2 (n = 336, 35%) and 3 (n = 240, 26%) groups showed relatively mild and moderate cognitive decline trajectories, respectively. Cluster 4, comprising about 11% of our study sample (n = 105), exhibited an aggressive cognitive decline trajectory and was characterized by a pronouncedly abnormal biomarker profile.

CONCLUSIONS

Individuals with MCI show substantial heterogeneity in cognitive decline. Our findings may potentially contribute to improved trial design and patient stratification.

R4Alz-Revised: A Tool Able to Strongly Discriminate 'Subjective Cognitive Decline' from Healthy Cognition and 'Minor Neurocognitive Disorder'

BACKGROUND

The diagnosis of the minor neurocognitive diseases in the clinical course of dementia before the clinical symptoms' appearance is the holy grail of neuropsychological research. The R4Alz battery is a novel and valid tool that was designed to assess cognitive control in people with minor cognitive disorders. The aim of the current study is the R4Alz battery's extension (namely R4Alz-R), enhanced by the design and administration of extra episodic memory tasks, as well as extra cognitive control tasks, towards improving the overall R4Alz discriminant validity.

METHODS

The study comprised 80 people: (a) 20 Healthy adults (HC), (b) 29 people with Subjective Cognitive Decline (SCD), and (c) 31 people with Mild Cognitive Impairment (MCI). The groups differed in age and educational level.

RESULTS

Updating, inhibition, attention switching, and cognitive flexibility tasks discriminated SCD from HC (p ≤ 0.003). Updating, switching, cognitive flexibility, and episodic memory tasks discriminated SCD from MCI (p ≤ 0.001). All the R4Alz-R's tasks discriminated HC from MCI (p ≤ 0.001). The R4Alz-R was free of age and educational level effects. The battery discriminated perfectly SCD from HC and HC from MCI (100% sensitivity-95% specificity and 100% sensitivity-90% specificity, respectively), whilst it discriminated excellently SCD from MCI (90.3% sensitivity-82.8% specificity).

CONCLUSION

SCD seems to be stage a of neurodegeneration since it can be objectively evaluated via the R4Alz-R battery, which seems to be a useful tool for early diagnosis.

Neurocognitive Operations Underlying Working Memory Abilities: An Analysis of Latency and Time-Based Parameters

BACKGROUND

The theory of executive attention (Fuster, 2015) suggests considerable plasticity regarding when specific neurocognitive operations are recruited to bring executive tasks to fruition.

OBJECTIVE

We tested the hypothesis that differing neurocognitive operations are recruited upon the initiation of a response, but that other distinct neurocognitive operations are recruited towards the middle or end of a response.

METHODS

The Backward Digit Span Test (BDST) was administered to 58 memory clinic patients (MCI, n = 22; no-MCI, n = 36). Latency to generate all correct 5-span responses was obtained. Statistical analyses found that optimal group classification was achieved using the first and third digit backward. First and third response latencies were analyzed in relation to verbal working memory (WM), visual WM, processing speed, visuospatial operations, naming/lexical access, and verbal episodic memory tests.

RESULTS

For the first response, slower latencies were associated with better performance in relation to verbal WM and visuospatial test performance. For the third response, faster latencies were associated with better processing speed and visuospatial test performance.

CONCLUSION

Consistent with the theory of executive attention, these data show that the neurocognitive operations underlying successful executive test performance are not monolithic but can be quite nuanced with differing neurocognitive operations associated with specific time epochs. Results support the efficacy of obtaining time-based latency parameters to help disambiguate successful executive neurocognitive operations in memory clinic patients.

The Test of Visuospatial Construction: A Novel Test of Non-motoric Visuoconstruction

Objective

The Test of Visuospatial Construction (TVSC) was designed as an easily administered measure of non-motor visuoconstruction, though only preliminary data exists regarding the clinical utility of this task. The current study examined the diagnostic accuracy of the TVSC by comparing performance between healthy subjects and various clinical groups. The authors also wanted to determine whether previous findings could be replicated regarding its effectiveness at tracking cognitive decline.

Method

Archival data collected over a period of more than 10 years were utilized and the overall sample consisted of 955 individuals, 372 healthy subjects, and 583 subjects who were categorized into various clinical groups. Only TVSC test data and demographic variables were utilized for statistical analyses in this study.

Results

The control group obtained significantly higher scores on the TVSC than the clinical groups. AUC values were indicative of excellent discrimination between cases and controls. Exploratory ROC curve analyses suggested adequate to excellent discrimination between the control group and the individual clinical groups as well as between the mild cognitive impairment (MCI) subgroups and the two dementia groups.

Conclusions

This study demonstrates that the TVSC can effectively differentiate between healthy subjects and neurologically compromised individuals. Additionally, the TVSC may be able to measure the progressive decline in visuoconstructive abilities that occurs as patients traverse the spectrum of MCI and dementia.

Disrupted Value-Directed Strategic Processing in Individuals with Mild Cognitive Impairment: Behavioral and Neural Correlates

Value-directed strategic processing involves attending to higher-value information while inhibiting lower-value information. This preferential processing is relatively preserved in cognitively normal older adults but is impaired in individuals with dementia. No studies have investigated whether value-directed strategic processing is disrupted in earlier stages of cognitive decline, namely, mild cognitive impairment (MCI). The current study examined behavioral and EEG differences in value-directed strategic processing between 18 individuals with MCI and 18 cognitively normal older controls using a value-directed list learning task. Behaviorally, individuals with MCI recalled fewer total and high-value words compared to controls, but no group differences were observed in low-value word recall. Neurally, individuals with MCI had reduced theta synchronization relative to controls between 100 and 200 ms post-stimulus. Greater alpha desynchronization was observed for high- versus low-value words between 300 and 400 ms in controls but not in the MCI group. The groups showed some processing similarities, with greater theta synchronization for low-value words between 700 and 800 ms and greater alpha desynchronization for high-value words between 500 and 1100 ms. Overall, value-directed strategic processing was compromised in individuals with MCI on both behavioral and neural measures relative to controls. These findings add to the growing body of literature on differences between typical cognitive aging and MCI.

Diagnosing Mild Cognitive Impairment Among Racially Diverse Older Adults: Comparison of Consensus, Actuarial, and Statistical Methods

BACKGROUND

Actuarial and statistical methods have been proposed as alternatives to conventional methods of diagnosing mild cognitive impairment (MCI), with the aim of enhancing diagnostic and prognostic validity, but have not been compared in racially diverse samples.

OBJECTIVE

We compared the agreement of consensus, actuarial, and statistical MCI diagnostic methods, and their relationship to race and prognostic indicators among diverse older adults.

METHODS

Participants (N = 354; M age = 71; 68% White, 29% Black) were diagnosed with MCI or normal cognition (NC) according to clinical consensus, actuarial neuropsychological criteria (Jak/Bondi), and latent class analysis (LCA). We examined associations with race/ethnicity, longitudinal cognitive and functional change, and incident dementia.

RESULTS

MCI rates by consensus, actuarial criteria, and LCA were 44%, 53%, and 41%, respectively. LCA identified three MCI subtypes (memory; memory/language; memory/executive) and two NC classes (low normal; high normal). Diagnostic agreement was substantial, but agreement of the actuarial method with consensus and LCA was weaker than the agreement between consensus and LCA. Among cases classified as MCI by actuarial criteria only, Black participants were over-represented, and outcomes were generally similar to those of NC participants. Consensus diagnoses best predicted longitudinal outcomes overall, whereas actuarial diagnoses best predicted longitudinal functional change among Black participants.

CONCLUSION

Consensus diagnoses optimize specificity in predicting dementia, but among Black older adults, actuarial diagnoses may be more sensitive to early signs of decline. Results highlight the need for cross-cultural validity in MCI diagnosis and should be explored in community- and population-based samples.

Data-Driven vs Consensus Diagnosis of MCI: Enhanced Sensitivity for Detection of Clinical, Biomarker, and Neuropathologic Outcomes

BACKGROUND AND OBJECTIVES

Given prior work demonstrating that mild cognitive impairment (MCI) can be empirically differentiated into meaningful cognitive subtypes, we applied actuarial methods to comprehensive neuropsychological data from the University of California San Diego Alzheimer's Disease Research Center (ADRC) in order to identify cognitive subgroups within ADRC participants without dementia and to examine cognitive, biomarker, and neuropathologic trajectories.

METHODS

Cluster analysis was performed on baseline neuropsychological data (n = 738; mean age 71.8). Survival analysis examined progression to dementia (mean follow-up 5.9 years). CSF Alzheimer disease (AD) biomarker status and neuropathologic findings at follow-up were examined in a subset with available data.

RESULTS

Five clusters were identified: optimal cognitively normal (CN; n = 130) with above-average cognition, typical CN (n = 204) with average cognition, nonamnestic MCI (naMCI; n = 104), amnestic MCI (aMCI; n = 216), and mixed MCI (mMCI; n = 84). Progression to dementia differed across MCI subtypes (mMCI > aMCI > naMCI), with the mMCI group demonstrating the highest rate of CSF biomarker positivity and AD pathology at autopsy. Actuarial methods classified 29.5% more of the sample with MCI and outperformed consensus diagnoses in capturing those who had abnormal biomarkers, progressed to dementia, or had AD pathology at autopsy.

DISCUSSION

We identified subtypes of MCI and CN with differing cognitive profiles, clinical outcomes, CSF AD biomarkers, and neuropathologic findings over more than 10 years of follow-up. Results demonstrate that actuarial methods produce reliable cognitive phenotypes, with data from a subset suggesting unique biological and neuropathologic signatures. Findings indicate that data-driven algorithms enhance diagnostic sensitivity relative to consensus diagnosis for identifying older adults at risk for cognitive decline.

Interindividual and intraindividual variability in amnestic mild cognitive impairment (aMCI) measured with an online cognitive assessment

INTRODUCTION

Mean cognitive performance is worse in amnestic mild cognitive impairment (aMCI) compared to control groups. However, studies on variability of cognitive performance in aMCI have yielded inconclusive results, with many differences in variability measures and samples from one study to another.

METHODS

We examined variability in aMCI using an existing older adult sample (n = 91; 51 with aMCI, 40 with normal cognition for age), measured with an online self-administered computerized cognitive assessment (Cogniciti's Brain Health Assessment). Our methodology extended past findings by using pure measures of variability (controlling for confounding effects of group performance or practice), and a clinically representative aMCI sample (reflecting the continuum of cognitive performance between normal cognition and aMCI).

RESULTS

Between-group t-tests showed significantly greater between-person variability (interindividual variability or diversity) in overall cognitive performance in aMCI than controls, although the effect size was with a small to moderate effect size, d = 0.44. No significant group differences were found in within-person variability (intraindividual variability) across cognitive tasks (dispersion) or across trials of a response time task (inconsistency), which may be because we used a sample measuring the continuum of cognitive performance. Exploratory correlation analyses showed that a worse overall score was associated with greater inter- and intraindividual variability, and that variability measures were correlated with each other, indicating people with worse cognitive performance were more variable.

DISCUSSION

The current study demonstrates that self-administered online tests can be used to remotely assess different types of variability in people at risk of Alzheimer`s. Our findings show small but significantly more interindividual differences in people with aMCI. This diversity is considered as "noise" in standard assessments of mean performance, but offers an interesting and cognitively informative "signal" in itself.

Latent Profile Analysis of Cognition in a Non-Demented Diverse Cohort: A Focus on Modifiable Cardiovascular and Lifestyle Factors

BACKGROUND

Cognitively-defined subgroups are well-documented within neurodegeneration.

OBJECTIVE

We examined such profiles in diverse non-demented older adults and considered how resulting subgroups relate to modifiable factors associated with neurodegeneration.

METHODS

121 non-demented (MMSE = 28.62) diverse (46%non-Latino Black, 40%non-Latino White, 15%Latino) community-dwelling adults (age = 67.7 years) completed cognitive, cardiovascular, physical activity, and diet evaluations. Latent profile analyses (LPA) employed six cognitive scores (letter fluency, letter-number sequencing, confrontational naming, 'animal' fluency, list-learning delayed recall, and recognition discriminability) to characterize cognitively-defined subgroups. Differences between resulting subgroups on cardiovascular (composite scores of overall health; specific health components including fasting blood levels) and lifestyle (sedentary behavior; moderate-to-vigorous physical activity; Mediterranean diet consumption) factors were examined using ANCOVAs adjusting for relevant confounders.

RESULTS

Based on sample means across cognitive scores, LPA resulted in the following cognitive subgroups: 1) high-average cognition, 55%non-Latino White and 64%female participants; 2) average cognition, 58%non-Latino Black and 68%male participants; 3) lower memory, 58%non-Latino Black participants; and 4) lower executive functioning, 70%Latinos. The high-average subgroup reported significantly higher Mediterranean diet consumption than the average subgroup (p = 0.001). The lower executive functioning group had higher fasting glucose and hemoglobin A1c than all other subgroups (p-values<0.001).

CONCLUSION

LPA revealed two average subgroups reflecting level differences in cognition previously reported between non-Latino White and Black adults, and two lower cognition subgroups in domains similar to those documented in neurodegeneration. These subgroups, and their differences, suggest the importance of considering social determinants of health in cognitive aging and modifiable risk.

Low-Frequency Transcranial Magnetic Stimulation (LF-TMS) in Treating Depression in Patients With Impaired Cognitive Functioning

OBJECTIVE

Common methodologies for treating depressive symptoms have demonstrated decreased efficacy among individuals with impaired cognitive functioning. While transcranial magnetic stimulation (TMS) has been approved to treat major depressive disorder, few studies have analyzed the ability of TMS to treat depressive symptoms among individuals with cognitive impairments. The present study had two objectives: to determine whether low-frequency TMS (LF-TMS) might demonstrate efficacy in treating depressive symptoms among individuals with impaired cognitive functioning; and to determine whether LF-TMS might improve neurocognitive functioning above and beyond depressive symptom improvements.

METHODS

Data were derived from a pre-existing database at Eastern Virginia Medical School. Fifty-three (N=53) participants completed LF-TMS treatment. The Beck Depression Inventory II (BDI-II) and CNS Vital Signs (CNS-VS) neurocognitive assessment were administered at multiple time points throughout treatment. Participants were classified as impaired cognitive functioning or average cognitive functioning based on baseline CNS-VS scores. Data were analyzed using restricted maximum likelihood (REML) measures-within-persons longitudinal hierarchical linear modeling (HLM) with time-varying covariates.

RESULTS

LF-TMS produced significant reductions in depressive symptoms for individuals in both cognitive functioning groups; however, a significant group-by-time interaction indicates differential effects between these two groups. Low-frequency TMS produced significant improvements in three neurocognitive domains above and beyond improvements in depressive symptoms; however, the reliability of these changes may be questionable.

CONCLUSIONS

This study adds to the growing body of empirical findings for LF-TMS treatment in improving neurocognitive functioning above and beyond other treatment-related effects.

Alzheimer's/Vascular Spectrum Dementia: Classification in Addition to Diagnosis

Alzheimer's disease (AD) and vascular dementia (VaD) are the two most common types of dementia. Although the combination of these disorders, called 'mixed' dementia, is recognized, the prevailing clinical and research perspective continues to consider AD and VaD as independent disorders. A review of recent neuropathological and neuropsychological literature reveals that these two disorders frequently co-occur and so-called 'pure' AD or VaD is comparatively rare. In addition, recent research shows that vascular dysfunction not only potentiates AD pathology, but that pathological changes in AD may subsequently induce vascular disorders. On the basis of these data, we propose that the neurobiological underpinnings underlying AD/VaD dementia and their neuropsychological phenotypes are best understood as existing along a clinical/pathological continuum or spectrum. We further propose that in conjunction with current diagnostic criteria, statistical modeling techniques using neuropsychological test performance should be leveraged to construct a system to classify AD/VaD spectrum dementia in order to test hypotheses regarding how mechanisms related to AD and VaD pathology interact and influence each other.

Cognitive Phenotypes of Older Adults with Subjective Cognitive Decline and Amnestic Mild Cognitive Impairment: The Czech Brain Aging Study

OBJECTIVE

To compare cognitive phenotypes of participants with subjective cognitive decline (SCD) and amnestic mild cognitive impairment (aMCI), estimate progression to MCI/dementia by phenotype and assess classification error with machine learning.

METHOD

Dataset consisted of 163 participants with SCD and 282 participants with aMCI from the Czech Brain Aging Study. Cognitive assessment included the Uniform Data Set battery and additional tests to ascertain executive function, language, immediate and delayed memory, visuospatial skills, and processing speed. Latent profile analyses were used to develop cognitive profiles, and Cox proportional hazards models were used to estimate risk of progression. Random forest machine learning algorithms reported cognitive phenotype classification error.

RESULTS

Latent profile analysis identified three phenotypes for SCD, with one phenotype performing worse across all domains but not progressing more quickly to MCI/dementia after controlling for age, sex, and education. Three aMCI phenotypes were characterized by mild deficits, memory and language impairment (dysnomic aMCI), and severe multi-domain aMCI (i.e., deficits across all domains). A dose-response relationship between baseline level of impairment and subsequent risk of progression to dementia was evident for aMCI profiles after controlling for age, sex, and education. Machine learning more easily classified participants with aMCI in comparison to SCD (8% vs. 21% misclassified).

CONCLUSIONS

Cognitive performance follows distinct patterns, especially within aMCI. The patterns map onto risk of progression to dementia.

Predementia constructs: Mild cognitive impairment or mild neurocognitive disorder? A narrative review

BACKGROUND

Predementia is a heuristic umbrella concept to classify older adults with cognitive impairment who do not suffer dementia. Many diagnostic entities have been proposed to address this concept, but most of them have not had widespread acceptance.

AIMS

To review clinical definitions, epidemiologic data (prevalence, incidence) and rate of conversion to dementia of the main predementia constructs, with special interest in the two most frequently used: mild cognitive impairment (MCI) and minor neurocognitive disorder (miNCD).

METHODS

We have selected in three databases (MEDLINE, Web of Science and Google scholar) the references from inception to 31 December 2019 of relevant reviews, population and community-based surveys, and clinical series with >500 participants and >3 years follow-up as the best source of evidence.

MAIN RESULTS

The history of predementia constructs shows that MCI is the most referred entity. It is widely recognized as a clinical syndrome harbinger of dementia of several etiologies, mainly MCI due to Alzheimer's disease. The operational definition of MCI has shortcomings: vagueness of its requirement of "preserved independence in functional abilities" and others. The recent miNCD construct presents analogous difficulties. Current data indicate that it is a stricter predementia condition, with lower prevalence than MCI, less sensitivity to cognitive decline and, possibly, higher conversion rate to dementia.

CONCLUSIONS

MCI is a widely employed research and clinical entity. Preliminary data indicate that the clinical use of miNCD instead of MCI requires more scientific evidence. Both approaches have common limitations that need to be addressed.

Structural Brain Imaging Phenotypes of Mild Cognitive Impairment (MCI) and Alzheimer's Disease (AD) Found by Hierarchical Clustering

A hierarchical clustering algorithm was applied to magnetic resonance images (MRI) of a cohort of 751 subjects having a mild cognitive impairment (MCI), 282 subjects having received Alzheimer's disease (AD) diagnosis, and 428 normal controls (NC). MRIs were preprocessed to gray matter density maps and registered to a stereotactic space. By first rendering the gray matter density maps comparable by regressing out age, gender, and years of education, and then performing the hierarchical clustering, we found clusters displaying structural features of typical AD, cortically-driven atypical AD, limbic-predominant AD, and early-onset AD (EOAD). Among these clusters, EOAD subjects displayed marked cortical gray matter atrophy and atrophy of the precuneus. Furthermore, EOAD subjects had the highest progression rates as measured with ADAS slopes during the longitudinal follow-up of 36 months. Striking heterogeneities in brain atrophy patterns were observed with MCI subjects. We found clusters of stable MCI, clusters of diffuse brain atrophy with fast progression, and MCI subjects displaying similar atrophy patterns as the typical or atypical AD subjects. Bidirectional differences in structural phenotypes were found with MCI subjects involving the anterior cerebellum and the frontal cortex. The diversity of the MCI subjects suggests that the structural phenotypes of MCI subjects would deserve a more detailed investigation with a significantly larger cohort. Our results demonstrate that the hierarchical agglomerative clustering method is an efficient tool in dividing a cohort of subjects with gray matter atrophy into coherent clusters manifesting different structural phenotypes.

Cognitive phenotypes 1 month after ICU discharge in mechanically ventilated patients: a prospective observational cohort study

BACKGROUND

ICU patients undergoing invasive mechanical ventilation experience cognitive decline associated with their critical illness and its management. The early detection of different cognitive phenotypes might reveal the involvement of diverse pathophysiological mechanisms and help to clarify the role of the precipitating and predisposing factors. Our main objective is to identify cognitive phenotypes in critically ill survivors 1 month after ICU discharge using an unsupervised machine learning method, and to contrast them with the classical approach of cognitive impairment assessment. For descriptive purposes, precipitating and predisposing factors for cognitive impairment were explored.

METHODS

A total of 156 mechanically ventilated critically ill patients from two medical/surgical ICUs were prospectively studied. Patients with previous cognitive impairment, neurological or psychiatric diagnosis were excluded. Clinical variables were registered during ICU stay, and 100 patients were cognitively assessed 1 month after ICU discharge. The unsupervised machine learning K-means clustering algorithm was applied to detect cognitive phenotypes. Exploratory analyses were used to study precipitating and predisposing factors for cognitive impairment.

RESULTS

K-means testing identified three clusters (K) of patients with different cognitive phenotypes: K1 (n = 13), severe cognitive impairment in speed of processing (92%) and executive function (85%); K2 (n = 33), moderate-to-severe deficits in learning-memory (55%), memory retrieval (67%), speed of processing (36.4%) and executive function (33.3%); and K3 (n = 46), normal cognitive profile in 89% of patients. Using the classical approach, moderate-to-severe cognitive decline was recorded in 47% of patients, while the K-means method accurately classified 85.9%. The descriptive analysis showed significant differences in days (p = 0.016) and doses (p = 0.039) with opioid treatment in K1 vs. K2 and K3. In K2, there were more women, patients were older and had more comorbidities (p = 0.001) than in K1 or K3. Cognitive reserve was significantly (p = 0.001) higher in K3 than in K1 or K2.

CONCLUSION

One month after ICU discharge, three groups of patients with different cognitive phenotypes were identified through an unsupervised machine learning method. This novel approach improved the classical classification of cognitive impairment in ICU survivors. In the exploratory analysis, gender, age and the level of cognitive reserve emerged as relevant predisposing factors for cognitive impairment in ICU patients.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier:NCT02390024; March 17,2015.

Identification of Patterns of Cognitive Impairment for Early Detection of Dementia

Early detection of dementia is crucial to devise effective interventions. Comprehensive cognitive tests, while being the most accurate means of diagnosis, are long and tedious, thus limiting their applicability to a large population, especially when periodic assessments are needed. The problem is compounded by the fact that people have differing patterns of cognitive impairment as they progress to different forms of dementia. This paper presents a novel scheme by which individual-specific patterns of impairment can be identified and used to devise personalized tests for periodic follow-up. Patterns of cognitive impairment are initially learned from a population cluster of combined normals and cognitively impaired subjects, using a set of standardized cognitive tests. Impairment patterns in the population are identified using a 2-step procedure involving an ensemble wrapper feature selection followed by cluster identification and analysis. These patterns have been shown to correspond to clinically accepted variants of Mild Cognitive Impairment (MCI), a prodrome of dementia. The learned clusters of patterns can subsequently be used to identify the most likely route of cognitive impairment, even for pre-symptomatic and apparently normal people. Baseline data of 24,000 subjects from the NACC database was used for the study.

Evidence for the Utility of Actuarial Neuropsychological Criteria Across the Continuum of Normal Aging, Mild Cognitive Impairment, and Dementia

Background:

Research suggests that actuarial neuropsychological criteria improve the accuracy of mild cognitive impairment (MCI) diagnoses relative to conventional diagnostic methods.

Objective:

We sought to examine the utility of actuarial criteria relative to consensus diagnostic methods used in the National Alzheimer’s Coordinating Center (NACC) Uniform Data Set (UDS), and more broadly across the continuum of normal aging, MCI, and dementia.

Methods:

We compared rates of cognitively normal (CN), MCI, and dementia diagnoses at baseline using actuarial versus consensus diagnostic methods in 1524 individuals from the NACC UDS.

Results:

Approximately one-third (33.59%) of individuals diagnosed as CN and more than one-fifth (22.03%) diagnosed with dementia based on consensus methods, met actuarial criteria for MCI. Many participants diagnosed with MCI via consensus methods also appeared to represent possible diagnostic errors. Notably, the CN_a/CN_c group (i.e., participants diagnosed as CN based on both actuarial [_a] and consensus [_c] criteria) had a lower proportion of apolipoprotein E ɛ4 carriers than the MCI_a/MCI_c group, which in turn had a lower proportion of ɛ4 carriers than the dementia (Dem)_a/Dem_c group. Proportions of ɛ4 carriers were comparable between the CN_a/CN_c and CN_a/MCI_c, MCI_a/MCI_c and MCI_a/CN_c, MCI_a/MCI_c and MCI_a/Dem_c, and Dem_a/Dem_c and Dem_a/MCI_c groups. These results were largely consistent with diagnostic agreement/discrepancy group comparisons on neuropsychological performance.

Conclusion:

The present results extend previous findings and suggest that actuarial neuropsychological criteria may enhance diagnostic accuracy relative to consensus methods, and across the wider continuum of normal aging, MCI, and dementia. Findings have implications for both clinical practice and research.

The Factor Structure of Cognitive Functioning in Cognitively Healthy Participants: a Meta-Analysis and Meta-Analysis of Individual Participant Data

Many neuropsychologists are of the opinion that the multitude of cognitive tests may be grouped into a much smaller number of cognitive domains. However, there is little consensus on how many domains exist, what these domains are, nor on which cognitive tests belong to which domain. This incertitude can be solved by factor analysis, provided that the analysis includes a broad range of cognitive tests that have been administered to a very large number of people. In this article, two such factor analyses were performed, each combining multiple studies. However, because it was not possible to obtain complete multivariate data on more than the most common test variables in the field, not all possible domains were examined here. The first analysis was a factor meta-analysis of correlation matrices combining data of 60,398 healthy participants from 52 studies. Several models from the literature were fitted, of which a version based on the Cattell-Horn-Carroll (CHC) model was found to describe the correlations better than the others. The second analysis was a factor analysis of the Advanced Neuropsychological Diagnostics Infrastructure (ANDI) database, combining scores of 11,881 participants from 54 Dutch and Belgian studies not included in the first meta-analysis. Again, the model fit was better for the CHC model than for other models. Therefore, we conclude that the CHC model best characterizes both cognitive domains and which test belongs to each domain. Therefore, although originally developed in the intelligence literature, the CHC model deserves more attention in neuropsychology.

Small World Index in Default Mode Network Predicts Progression from Mild Cognitive Impairment to Dementia

Aim of this study was to explore the EEG functional connectivity in amnesic mild cognitive impairments (MCI) subjects with multidomain impairment in order to characterize the Default Mode Network (DMN) in converted MCI (cMCI), which converted to Alzheimer’s disease (AD), compared to stable MCI (sMCI) subjects. A total of 59 MCI subjects were recruited and divided -after appropriate follow-up- into cMCI or sMCI. They were further divided in MCI with linguistic domain (LD) impairment and in MCI with executive domain (ED) impairment. Small World (SW) index was measured as index of balance between integration and segregation brain processes. SW, computed restricting to nodes of DMN regions for all frequency bands, evaluated how they differ between MCI subgroups assessed through clinical and neuropsychological four-years follow-up. In addition, SW evaluated how this pattern differs between MCI with LD and MCI with ED. Results showed that SW index significantly decreased in gamma band in cMCI compared to sMCI. In cMCI with LD impairment, the SW index significantly decreased in delta band, while in cMCI with ED impairment the SW index decreased in delta and gamma bands and increased in alpha1 band. We propose that the DMN functional alterations in cognitive impairment could reflect an abnormal flow of brain information processing during resting state possibly associated to a status of pre-dementia.

Latent Cognitive Profiles Differ Between Incipient Alzheimer's Disease and Dementia with Subcortical Vascular Lesions in a Memory Clinic Population

BACKGROUND

It is unclear if latent cognitive profiles can distinguish between dementia with subcortical vascular lesions and Alzheimer's disease (AD) at the incipient stage, and if they differ in performance from the Petersen subtypes.

OBJECTIVE

To identify latent cognitive profiles in a naturalistic population of patients from a memory clinic sample, and investigate the derived classes not only in terms of conversion to AD, but also in terms of conversion to dementia with subcortical vascular lesions. Another objective was to compare the derived classes to the Petersen subtypes.

METHODS

We performed a latent profile analysis (LPA) on standardized neuropsychological test scores from 476 memory clinic patients (age 64±8) without dementia, and analyzed progression to dementia after 2 years.

RESULTS

The LPA resulted in two classes with impaired cognition (Amnestic and Slow/Dysexecutive) and two classes with normal cognition (Normal-Low and Normal-High cognition). Belonging to the Amnestic class predicted progression to all-cause dementia and to AD; belonging to the Slow/Dysexecutive class predicted progression to all-cause dementia, AD, and dementia with subcortical vascular lesions. Of the Petersen MCI subtypes, only amnestic multi-domain MCI predicted progression to all-cause dementia, AD, and dementia with subcortical vascular lesions.

CONCLUSION

Latent cognitive profiles separated between AD and dementia with subcortical vascular lesions, while the Petersen subtypes did not. However, similar to the Petersen subtypes, LPA classes work better for ruling out progression to dementia than for case finding.

Breadth and depth of working memory and executive function compromises in mild cognitive impairment and their relationships to frontal lobe morphometry and functional competence

INTRODUCTION

The extent of working memory (WM) and executive function (EF) impairment in mild cognitive impairment (MCI) is not well-characterized.

METHODS

We compared 48 patients with MCI, 124 noncognitively impaired elderly healthy controls, and 57 patients with Alzheimer's disease (AD) on multiple WM/EF measures, frontal lobe integrity indexes, and functioning.

RESULTS

Patients with MCI demonstrated worse performance on nearly all WM/EF tests. This profile of impairment was refined in a factor analysis that identified three primary WM/EF constructs: WM storage; speed and controlled visual search; and manipulation of information and problem solving. EF impairments were associated with reductions in prefrontal cortical thickness. WM/EF accounted for over 50% of the variance in functional competence.

DISCUSSION

In MCI, WM/EF impairments are far from rare, based on specific compromises to frontal cortex circuitry, and are associated with loss of everyday functioning. WM/EF impairments, even at this potentially prodromal stage of AD, have clinically deleterious consequences.

Does Empirically Derived Classification of Individuals with Subjective Cognitive Complaints Predict Dementia?

(1) Background: Early identification of mild cognitive impairment (MCI) in people reporting subjective cognitive complaints (SCC) and the study of progression of cognitive decline are important issues in dementia research. This paper examines whether empirically derived procedures predict progression from MCI to dementia. (2) Methods: At baseline, 192 participants with SCC were diagnosed according to clinical criteria as cognitively unimpaired (70), single-domain amnestic MCI (65), multiple-domain amnestic MCI (33) and multiple-domain non-amnestic MCI (24). A two-stage hierarchical cluster analysis was performed for empirical classification. Categorical regression analysis was then used to assess the predictive value of the clusters obtained. Participants were re-assessed after 36 months. (3) Results: Participants were grouped into four empirically derived clusters: Cluster 1, similar to multiple-domain amnestic MCI; Cluster 2, characterized by subjective cognitive decline (SCD) but with low scores in language and working memory; Cluster 3, with specific deterioration in episodic memory, similar to single-domain amnestic MCI; and Cluster 4, with SCD but with scores above the mean in all domains. The majority of participants who progressed to dementia were included in Cluster 1. (4) Conclusions: Cluster analysis differentiated between MCI and SCD in a sample of people with SCC and empirical criteria were more closely associated with progression to dementia than standard criteria.

Grant Report on PREDICT-ADFTD: Multimodal Imaging Prediction of AD/FTD and Differential Diagnosis

We report on the ongoing project "PREDICT-ADFTD: Multimodal Imaging Prediction of AD/FTD and Differential Diagnosis" describing completed and future work supported by this grant. This project is a multi-site, multi-study collaboration effort with research spanning seven sites across the US and Canada. The overall goal of the project is to study neurodegeneration within Alzheimer's Disease, Frontotemporal Dementia, and related neurodegenerative disorders, using a variety of brain imaging and computational techniques to develop methods for the early and accurate prediction of disease and its course. The overarching goal of the project is to develop the earliest and most accurate biomarker that can differentiate clinical diagnoses to inform clinical trials and patient care. In its third year, this project has already completed several projects to achieve this goal, focusing on (1) structural MRI (2) machine learning and (3) FDG-PET and multimodal imaging. Studies utilizing structural MRI have identified key features of underlying pathology by studying hippocampal deformation that is unique to clinical diagnosis and also post-mortem confirmed neuropathology. Several machine learning experiments have shown high classification accuracy in the prediction of disease based on Convolutional Neural Networks utilizing MRI images as input. In addition, we have also achieved high accuracy in predicting conversion to DAT up to five years in the future. Further, we evaluated multimodal models that combine structural and FDG-PET imaging, in order to compare the predictive power of multimodal to unimodal models. Studies utilizing FDG-PET have shown significant predictive ability in the prediction and progression of disease.

Effect of computerised cognitive training on cognitive outcomes in mild cognitive impairment: a systematic review and meta-analysis

OBJECTIVES

To determine the effect of computerised cognitive training (CCT) on improving cognitive function for older adults with mild cognitive impairment (MCI).

DESIGN

Systematic review and meta-analysis.

DATA SOURCES

PubMed, Embase, Web of Science and the Cochrane Library were searched through January 2018.

ELIGIBILITY CRITERIA

Randomised controlled trials comparing CCT with control conditions in those with MCI aged 55+ were included.

DATA EXTRACTION AND SYNTHESIS

Two independent reviewers extracted data and assessed the risk of bias. Effect sizes (Hedges' g and 95% CIs) were calculated and random-effects meta-analyses were performed where three or more studies investigated a comparable intervention and outcome. Heterogeneity was quantified using the I2 statistic.

RESULTS

18 studies met the inclusion criteria and were included in the analyses, involving 690 participants. Meta-analysis revealed small to moderate positive treatment effects compared with control interventions in four domains as follows: global cognitive function (g=0.23, 95% CI 0.03 to 0.44), memory (g=0.30, 95% CI 0.11 to 0.50), working memory (g=0.39, 95% CI 0.12 to 0.66) and executive function (g=0.20, 95% CI -0.03 to 0.43). Statistical significance was reached in all domains apart from executive function.

CONCLUSIONS

This meta-analysis provides evidence that CCT improves cognitive function in older people with MCI. However, the long-term transfer of these improvements and the potential to reduce dementia prevalence remains unknown. Various methodological issues such as heterogeneity in outcome measures, interventions and MCI symptoms and lack of intention-to-treat analyses limit the quality of the literature and represent areas for future research.

Neuropsychological subtypes of incident mild cognitive impairment in the Mayo Clinic Study of Aging

INTRODUCTION

We evaluated whether incident mild cognitive impairment (MCI) subtypes could be empirically derived in the Mayo Clinic Study of Aging.

METHODS

We performed cluster analysis on neuropsychological data from 506 participants with incident MCI.

RESULTS

The 3-cluster solution resulted in (1) amnestic, (2) dysexecutive, (3) dysnomic subtypes. The 4-cluster solution produced these same three groups and a fourth group with subtle cognitive impairment (SCI). The SCI cluster was a subset of the amnestic cluster and distinct from well-matched cognitively unimpaired participants based on memory and global z-score area under the receiver operating characteristic curve analyses and probability of progression to MCI/dementia.

DISCUSSION

We empirically identified three neuropsychological subtypes of MCI that share some features with MCI subtypes identified in the Alzheimer's Disease Neuroimaging Initiative. The fourth subtype with SCI in the Mayo Clinic Study of Aging differed from the fourth cluster-derived normal group in Alzheimer's Disease Neuroimaging Initiative and could represent a group to target with early interventions.

Predicting conversion from mild cognitive impairment to Alzheimer's disease using brain 1H-MRS and volumetric changes: A two- year retrospective follow-up study

This study investigated the ability of magnetic resonance spectroscopy (¹H-MRS) of posterior cingulate cortex (PCC) and brain volumetry to predict the progression from mild cognitive impairment (MCI) to Alzheimer's Disease (AD) on the basis of clinical classification at 2 years follow-up. Thirty-eight MCI patients, eighteen healthy older adults and twenty-three AD patients were included in this study. All participants underwent a brain-MR protocol (1.5 T GE scanner) including high-resolution T1-weighted volumetric sequence (isotropic 1mm³). Voxel-wise differences in brain volumetry were evaluated using FreeSurfer software and all volumes were normalized by the total intracranial volume (TIV). Careful localization of ¹H-MRS volume of PCC was performed and data were processed with the LCModel program. MCI patients underwent a complete neuropsychological assessment at baseline and were clinically re-evaluated after a mean of 28 months; twenty-six MCI patients (68.4%) converted to AD and twelve remained stable.

At baseline these two MCI subgroups did not differ in the global cognitive level (Mini Mental State Examination, MMSE) or in any of the other cognitive domains; the NAA/ mI ratio in the PCC was able to differentiate MCI converters from those MCI that did not develop AD (p = 0.022) with a level of accuracy (AUC area) of 0.779. A significantly reduced volume of parahippocampal gyrus (p = 0.010) and fusiform gyrus (p = 0.026) were found in the converter MCI subgroup compared to the stable MCI subgroup. The combined use of both N- acetyl-aspartate (NAA)/myo-Inositol (mI) ratio and volume of parahippocampal gyrus, increases the overall accuracy (AUC = 0.910) in predicting the conversion to AD two years before the development of clinical symptoms. Additional longitudinal studies with a broader representative sample of MCI patients and longer follow-up might be helpful to confirm these results and to elucidate the role of each parameter in predicting the possible progression to AD, and also to all the other non-AD dementia subtypes.

•

Alterations of NAA/ml ratio in the PCC show high accuracy in predicting the progression to AD.

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Volume reduction of parahippocampal and fusiform gyrus are able to distinguish stable from converter MCI.

•

The combined use of both NAA/mI ratio and volume of parahippocampal gyrus increases the accuracy.

Differences in self-awareness of functional deficits between amnestic single- and multidomain mild cognitive impairment

INTRODUCTION

Prior research examining self-awareness of deficits in those with mild cognitive impairment (MCI) has been inconsistent, suggesting that preservation of insight at this disease stage may be conditional on the domain(s) examined as well as individual characteristics. The current study is the first to examine differences in objective performance and self-awareness of difficulties between older adults with amnestic single- (MCI-ASD) and multidomain MCI (MCI-AMD) across six instrumental activities of daily living (IADLs).

METHOD

Seventy-five individuals (M_age = 73.9 years, range = 55-88 years; 56% female) with MCI-ASD (n = 30) and MCI-AMD (n = 45) were recruited primarily from a hospital-based memory disorders clinic. Participants were administered self-report and objective measures assessing six functional domains: financial management, driving, telephone use, nutrition evaluation, grocery shopping, and medication management. Self-awareness discrepancy scores were calculated for each of these IADLs, and participants were classified as either "overestimating ability" or "accurately/underestimating ability."

RESULTS

Individuals with MCI-AMD performed significantly worse on objective measures of financial management, driving, and nutrition evaluation than those with MCI-ASD. Across MCI subtypes, participants were most likely to lack awareness of their difficulties in nutrition evaluation (31%), financial management (25%), and driving (23%) domains. Individuals with MCI-AMD were significantly more likely than those with MCI-ASD to overestimate performance on driving and telephone use domains.

CONCLUSION

Individuals with MCI-AMD are more likely than those with MCI-ASD to have impairment in their everyday function and to lack awareness into their IADL difficulties. When possible, clinicians should obtain objective measures in combination with detailed informant reports of functional abilities in order to evaluate capacity to independently engage in various daily activities. Finally, level of self-awareness varies across IADL domains, providing further evidence that insight is not a unitary construct.

Reversible predictors of reversion from mild cognitive impairment to normal cognition: a 4-year longitudinal study

BACKGROUND

Although previous studies have revealed many factors related to mild cognitive impairment (MCI) reversion, information about reversible factors related MCI reversion is limited, impeding the development of intervention strategies. The aim of the present study was to examine whether reversible factors such as lifestyle activities are associated with MCI reversion in elderly individuals using the National Center for Geriatrics and Gerontology-Study of Geriatric Syndromes database. A total of 396 community-living older adults (age ≥ 65 years) participated in the study. They were classified as reverters or non-reverters from mild cognitive impairment to normal cognition. We assessed lifestyle activities, potential confounding factors of cognitive decline, and reversion of mild cognitive impairment.

RESULTS

In a completed data set of 396 participants, 202 participants (51.0%) reverted from MCI to normal cognition. The reversion rate in participants for whom we imputed data was 34.3%. In the imputed group, a logistic regression model showed that the odds ratios (ORs) for reversion were significantly higher in participants who drove a car (OR 1.50, 95% confidence interval (CI) 1.41-1.60), used a map to travel to unfamiliar places (OR 1.12, 95% CI 1.06-1.18), read books or newspapers (OR 1.54, 95% CI 1.37-1.73), took cultural classes (OR 1.10, 95% CI 1.04-1.15), attended meetings in the community (OR 1.22, 95% CI 1.16-1.28), participated in hobbies or sports activities (OR 1.09, 95% CI 1.03-1.16), and engaged in fieldwork or gardening (OR 1.14, 95% CI 1.08-1.21). The imputed sample showed that non-reverters were more likely to discontinue fieldwork or gardening (11.0% vs. 6.1%) than reverters during the follow-up period.

CONCLUSIONS

Specific lifestyle activities may play important roles in MCI reversion in older adults. The longitudinal data indicate that it is reasonable to recommend that individuals continue to engage in fieldwork or gardening to increase their chance of recovery from MCI.

Assessing Working Memory in Mild Cognitive Impairment with Serial Order Recall

BACKGROUND

Working memory (WM) is often assessed with serial order tests such as repeating digits backward. In prior dementia research using the Backward Digit Span Test (BDT), only aggregate test performance was examined.

OBJECTIVE

The current research tallied primacy/recency effects, out-of-sequence transposition errors, perseverations, and omissions to assess WM deficits in patients with mild cognitive impairment (MCI).

METHODS

Memory clinic patients (n = 66) were classified into three groups: single domain amnestic MCI (aMCI), combined mixed domain/dysexecutive MCI (mixed/dys MCI), and non-MCI where patients did not meet criteria for MCI. Serial order/WM ability was assessed by asking participants to repeat 7 trials of five digits backwards. Serial order position accuracy, transposition errors, perseverations, and omission errors were tallied.

RESULTS

A 3 (group)×5 (serial position) repeated measures ANOVA yielded a significant group×trial interaction. Follow-up analyses found attenuation of the recency effect for mixed/dys MCI patients. Mixed/dys MCI patients scored lower than non-MCI patients for serial position 3 (p < 0.003) serial position 4 (p < 0.002); and lower than both group for serial position 5 (recency; p < 0.002). Mixed/dys MCI patients also produced more transposition errors than both groups (p < 0.010); and more omissions (p < 0.020), and perseverations errors (p < 0.018) than non-MCI patients.

CONCLUSIONS

The attenuation of a recency effect using serial order parameters obtained from the BDT may provide a useful operational definition as well as additional diagnostic information regarding working memory deficits in MCI.

Levels of plasma neurofilament light chain and cognitive function in patients with Alzheimer or Parkinson disease

Plasma neurofilament light (NFL) has been proposed as a blood-based biomarker for neurodegeneration in Alzheimer's disease (AD) and parkinsonian disorders. However, the relationship between plasma NFL and cognitive decline in dementia due to Parkinson's disease (PD) remains to be elucidated. In this research, 119 AD, 56 mild cognitive impairment (MCI), 26 non-demented PD (PDND), and 23 Parkinson's disease dementia (PDD) patients, as well as 59 cognitively healthy controls (HC) were recruited. Each subject underwent a battery of neuropsychological testing. Plasma NFL levels were measured in duplicate using an NF-Light assay and transferred onto the Simoa platform with a home-brew kit. Plasma NFL was significantly increased in the AD group, compared with the control, MCI, PDND, and PDD groups. Plasma NFL was significantly higher in the PDD group, compared with the PDND group. High plasma NFL correlated with poor cognition in AD and PD, but not with motor symptoms in PD. Plasma NFL may represent a biomarker of cognitive decline in AD and PD, with more specificity for AD.

Potential Role of OERP as Early Marker of Mild Cognitive Impairment

Olfactory impairment is present in up to 90% of patients with Alzheimer's disease (AD) and is present in certain cases of mild cognitive impairment (MCI), a transient phase between normal aging and dementia. Subjects affected by MCI have a higher risk of developing dementia compared to the general population, and studies have found that olfactory deficits could be an indicator of whether such a conversion might happen. Following these assumptions, aim of this study was to investigate olfactory perception in MCI patients. We recruited 12 MCI subjects (mean age 70 ± 6.7 years) through the Alzheimer Assessment Unit (UVA Unite) of ASL Lecce (Italy), and 12 healthy geriatric volunteers (HS) as the control group (mean age 64 ± 6.0 years), all of whom were first evaluated via a panel of neuropsychological tests. Subjects were asked to perform an olfactory recognition task involving two scents: rose and eucalyptus, administrated in the context of an oddball task during EEG recordings. Olfactory event-related potential (OERP) components N1 and Late Positive Potential (LPC) were then analyzed as measures of the sensorial and perceptive aspects of the olfactory response, respectively. It was determined that, in the MCI group, both the N1 and LPC components were significantly different compared to those of the HS group during the execution of the oddball task. In particular, the N1 amplitude, was reduced, while the LPC amplitude was increased, indicating that a degree of perceptive compensation can occur when sensorial function is impaired. Further, a correlation analysis, involving OERP components and neuropsychological battery scores, indicated that impairment of olfactory perception may share common pathways with impairments of the spatial system and long-term memory processing.

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).

Comprehensive Neuropsychological Assessment of Cognitive Functioning of Adults With Lower Limb Amputation in Rehabilitation

OBJECTIVE

To establish a comprehensive profile of cognitive functioning in people engaged in lower limb amputation (LLA) rehabilitation.

DESIGN

Cross-sectional study as part of a longitudinal prospective cohort.

SETTING

A national tertiary rehabilitation hospital.

PARTICIPANTS

Adult volunteer participants (N=87) referred for comprehensive rehabilitation for major LLA were sampled from 207 consecutive admissions. Participants with both vascular (n=69) and nonvascular (n=18) LLA etiologies were included.

INTERVENTIONS

Not applicable.

MAIN OUTCOME MEASURES

Demographic and health information and a battery of standardized neuropsychological assessments.

RESULTS

Compared to normative data, impairment was evident in overall cognitive functioning (P≤.003). Impairment was also evident in particular areas, including reasoning, psychomotor function, information processing, attention, memory, language/naming, visuospatial functions, and executive functions (all P≤.003 Holm-corrected). There were also higher frequencies of impaired functions across most aspects of functioning in this group compared with expected frequencies in normative data (P≤.003 Holm-corrected). There were no significant differences in cognitive functioning between participants of vascular and nonvascular LLA etiology.

CONCLUSIONS

Findings support the need for cognitive screening at rehabilitation admission regardless of etiology. Administration of comprehensive neuropsychological assessment with a battery sensitive to vascular cognitive impairment is recommended in some cases to generate an accurate and precise understanding of relative strengths and weaknesses in cognitive functioning. Cognitive functioning is a potential intervention point for improvement of rehabilitation outcomes for those with LLA, and further research is warranted in this area.

Identification of Heterogeneous Cognitive Subgroups in Community-Dwelling Older Adults: A Latent Class Analysis of the Einstein Aging Study

OBJECTIVES

The aim of this study was to identify natural subgroups of older adults based on cognitive performance, and to establish each subgroup's characteristics based on demographic factors, physical function, psychosocial well-being, and comorbidity.

METHODS

We applied latent class (LC) modeling to identify subgroups in baseline assessments of 1345 Einstein Aging Study (EAS) participants free of dementia. The EAS is a community-dwelling cohort study of 70+ year-old adults living in the Bronx, NY. We used 10 neurocognitive tests and 3 covariates (age, sex, education) to identify latent subgroups. We used goodness-of-fit statistics to identify the optimal class solution and assess model adequacy. We also validated our model using two-fold split-half cross-validation.

RESULTS

The sample had a mean age of 78.0 (SD=5.4) and a mean of 13.6 years of education (SD=3.5). A 9-class solution based on cognitive performance at baseline was the best-fitting model. We characterized the 9 identified classes as (i) disadvantaged, (ii) poor language, (iii) poor episodic memory and fluency, (iv) poor processing speed and executive function, (v) low average, (vi) high average, (vii) average, (viii) poor executive and poor working memory, (ix) elite. The cross validation indicated stable class assignment with the exception of the average and high average classes.

CONCLUSIONS

LC modeling in a community sample of older adults revealed 9 cognitive subgroups. Assignment of subgroups was reliable and associated with external validators. Future work will test the predictive validity of these groups for outcomes such as Alzheimer's disease, vascular dementia and death, as well as markers of biological pathways that contribute to cognitive decline. (JINS, 2018, 24, 511-523).

Mild cognitive impairment and prospective memory: translating the evidence into neuropsychological practice

OBJECTIVE

There has been a recent rapid development of research characterizing prospective memory performance in mild cognitive impairment (MCI) in older age. However, this body of literature remains largely separated from routine clinical practice in neuropsychology. Furthermore, there is emerging evidence of effective interventions to improve prospective memory performance. Therefore, our objective in this article was to offer a clinical neuropsychological perspective on the existing research in order to facilitate the translation of the evidence-base into clinical practice.

METHOD

By conducting a critical review of the existing research related to prospective memory and MCI, we highlight how this data can be introduced into clinical practice, either within diagnostic assessment or clinical management.

CONCLUSIONS

Prospective memory is impaired in older adults with MCI, with a pattern of performance that helps with differential diagnosis from healthy aging. Clinical neuropsychologists are encouraged to add prospective memory assessment to their toolbox for diagnostic evaluation of clients with MCI. Preliminary findings of prospective memory interventions in MCI are promising, but more work is required to determine how different approaches translate to increasing independence in everyday life.

Cognitive Efficiency in Alzheimer's Disease is Associated with Increased Occipital Connectivity

There are cognitive domains which remain fully functional in a proportion of Alzheimer's disease (AD) patients. It is unknown, however, what distinctive mechanisms sustain such efficient processing. The concept of "cognitive efficiency" was investigated in these patients by operationalizing it as a function of the level of performance shown on the Letter Fluency test, on which, very often, patients in the early stages of AD show unimpaired performance. Forty-five individuals at the prodromal/early stage of AD (diagnosis supported by subsequent clinical follow-ups) and 45 healthy controls completed a battery of neuropsychological tests and an MRI protocol which included resting state acquisitions. The Letter Fluency test was the only task on which no between-group difference in performance was found. Participants were divided into "low-performing" and "high-performing" according to the global median. Dual-regression methods were implemented to compute six patterns of network connectivity. The diagnosis-by-level of performance interaction was inferred on each pattern to determine the network distinctiveness of efficient performance in AD. Significant interactions were found in the anterior default mode network, and in both left and right executive control networks. For all three circuits, high-performing patients showed increased connectivity within the ventral and dorsal part of BA19, as confirmed by post hoc t tests. Peristriate remapping is suggested to play a compensatory role. Since the occipital lobe is the neurophysiological source of long-range cortical connectivity, it is speculated that the physiological mechanisms of functional connectivity might sustain occipital functional remapping in early AD, particularly for those functions which are sustained by areas not excessively affected by the prodromal disease.

Class-Specific Incidence of All-Cause Dementia and Alzheimer's Disease: A Latent Class Approach

Identifying preclinical Alzheimer's disease (AD) is an important step toward developing approaches to early treatment and dementia prevention. We applied latent class analysis (LCA) to 10 baseline neuropsychological assessments for 1,345 participants from Einstein Aging Study. Time-to-event models for all-cause dementia and AD were run examining events in 4-year intervals. Five classes were identified: Mixed-Domain Impairment (n = 107), Memory-Specific Impairment (n = 457), Average (n = 539), Frontal Impairment (n = 118), and Superior Cognition (n = 124). Compared to the Average class, the Mixed-Domain Impairment and Memory-Specific Impairment classes were at higher risk of incident all-cause dementia and AD in the first 4 years from baseline, while the Frontal Impairment class was associated with higher risk between 4 and 8 years of follow-up. LCA identified classes which differ in cross-sectional cognitive patterns and in risk of dementia over specific follow-up intervals.

Subjective rating of executive functions in mild Alzheimer's disease

OBJECTIVES

Subjective cognitive decline is considered to be a core feature of pre-Alzheimer's disease (AD) conditions, the vast majority of literature having focused on memory concerns. Neuropsychological studies have implicated executive dysfunction on objective performance measures in AD, but no research has evaluated whether individuals with AD have concerns about their executive functions and whether it differs from their caregiver's concerns. In the present study, we sought to evaluate self- and informant ratings of executive functioning in patients with mild AD.

METHOD

Participants were 23 patients with mild AD and 32 healthy elderly controls (HC) and their informants who completed the Behavior Rating Inventory of Executive Function - Adult version.

RESULTS

Patients with AD and their informants reported greater executive dysfunction than the HC group and their informants, respectively, and patients reported greater difficulty than their informants. The largest effect size for both self- and informant ratings was obtained for the Working Memory scale.

CONCLUSIONS

These findings indicate that subjective cognitive concerns in mild AD extend beyond the memory domain to executive functions. That greater difficulty was endorsed by patients than their informants suggests that at least in the mild stage of AD some awareness of executive dysfunction may be maintained in some patients. Implications for clinical care are discussed.

Problems in Classifying Mild Cognitive Impairment (MCI): One or Multiple Syndromes?

As the conceptual, methodological, and technological advances applied to dementias have evolved the construct of mild cognitive impairment (MCI), one problem encountered has been its classification into subtypes. Here, we aim to revise the concept of MCI and its subtypes, addressing the problems of classification not only from the psychometric point of view or by using alternative methods, such as latent class analysis, but also considering the absence of normative data. In addition to the well-known influence of certain factors on cognitive function, such as educational level and cultural traits, recent studies highlight the relevance of other factors that may significantly affect the genesis and evolution of MCI: subjective memory complaints, loneliness, social isolation, etc. The present work will contemplate the most relevant attempts to clarify the issue of MCI categorization and classification, combining our own data with that from recent studies which suggest the role of relevant psychosocial factors in MCI.

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).

Heterogeneity of Neuropsychological Impairment in HIV Infection: Contributions from Mild Cognitive Impairment

Despite longstanding acknowledgement of the heterogeneity of HIV-associated neurocognitive disorders (HAND), existing HAND diagnostic methods classify according to the degree of impairment, without regard to the pattern of neuropsychological strengths and weaknesses. Research in mild cognitive impairment (MCI) has demonstrated that classifying individuals into subtypes by both their level and pattern of impairment, using either conventional or statistical methods, has etiologic and prognostic utility. Methods for characterizing the heterogeneity of MCI provide a framework that can be applied to other disorders and may be useful in clarifying some of the current challenges in the study of HAND. A small number of studies have applied these methods to examine the heterogeneity of neurocognitive function among individuals with HIV. Most have supported the existence of multiple subtypes of neurocognitive impairment, with some evidence for distinct clinicodemographic features of these subtypes, but a number of gaps exist. Following a review of diagnostic methods and challenges in the study of HAND, we summarize the literature regarding conventional and empirical subtypes of MCI and HAND and identify directions for future research regarding neurocognitive heterogeneity in HIV infection.

Cortical Amyloid Burden Differences Across Empirically-Derived Mild Cognitive Impairment Subtypes and Interaction with APOE ɛ4 Genotype

We examined cortical amyloid-β (Aβ) levels and interactions with apolipoprotein (APOE) ɛ4 genotype status across empirically-derived mild cognitive impairment (MCI) subgroups and cognitively normal older adults. Participants were 583 ADNI participants (444 MCI, 139 normal controls [NC]) with baseline florbetapir positron emission tomography (PET) amyloid imaging and neuropsychological testing. Of those with ADNI-defined MCI, a previous cluster analysis [1] classified 51% (n = 227) of the current sample as amnestic MCI, 8% (n = 37) as dysexecutive/mixed MCI, and 41% (n = 180) as cluster-derived normal (cognitively normal). Results demonstrated that the dysexecutive/mixed and amnestic MCI groups showed significantly greater levels of amyloid relative to the cluster-derived normal and NC groups who did not differ from each other. Additionally, 78% of the dysexecutive/mixed, 63% of the amnestic MCI, 42% of the cluster-derived normal, and 34% of the NC group exceeded the amyloid positivity threshold. Finally, a group by APOE genotype interaction demonstrated that APOE ɛ4 carriers within the amnestic MCI, cluster-derived normal, and NC groups showed significantly greater amyloid accumulation compared to non-carriers of their respective group. Such an interaction was not revealed within the dysexecutive/mixed MCI group which was characterized by both greater cognitive impairment and amyloid accumulation compared to the other participant groups. Our results from the ADNI cohort show considerable heterogeneity in Aβ across all groups studied, even within a group of robust NC participants. Findings suggest that conventional criteria for MCI may be susceptible to false positive diagnostic errors, and that onset of Aβ accumulation may occur earlier in APOE ɛ4 carriers compared to non-carriers.