Single-domain amnestic mild cognitive impairment identified by cluster analysis predicts Alzheimer's disease in the european prospective DESCRIPA study

Clusters of cognitive performance predict long-term cognitive impairment in elderly patients with subjective memory complaints and healthy controls

INTRODUCTION

Patients with subjective memory complaints (SMC) may include subgroups with different neuropsychological profiles and risks of cognitive impairment.

METHODS

Cluster analysis was performed on two datasets (n: 630 and 734) comprising demographic and neuropsychological data from SMC and healthy controls (HC). Survival analyses were conducted on clusters. Bayesian model averaging assessed the predictive utility of clusters and other biomarkers.

RESULTS

Two clusters with higher and lower than average cognitive performance were detected in SMC and HC. Assignment to the lower performance cluster increased the risk of cognitive impairment in both datasets (hazard ratios: 1.78 and 2.96; Plog-rank: 0.04 and <0.001) and was associated with lower hippocampal volumes and higher tau/amyloid beta 42 ratios in cerebrospinal fluid. The effect of SMC was small and confounded by mood.

DISCUSSION

This study provides evidence of the presence of cognitive clusters that hold biological significance and predictive value for cognitive decline in SMC and HC.

HIGHLIGHTS

Patients with subjective memory complaints include two cognitive clusters. Assignment to the lower performance cluster increases risk of cognitive impairment. This cluster shows a pattern of biomarkers consistent with incipient Alzheimer's disease pathology. The same cognitive cluster structure is found in healthy controls. The effect of memory complaints on risk of cognitive decline is small and confounded.

Comparing three neuropsychological subgrouping approaches in subjective and mild cognitive impairment from a naturalistic multicenter study

Subjective cognitive impairment (SCI) and mild cognitive impairment (MCI) are two clinical groups with an increased risk to develop dementia, but they are highly heterogeneous. This study compared three different approaches to subgroup SCI and MCI patients and investigated their capacity to disentangle cognitive and biomarker heterogeneity. We included 792 patients from the MemClin-cohort (142 SCI and 650 MCI). Biomarkers included cerebrospinal fluid measures of beta-amyloid-42 and phosphorylated tau, as well as visual ratings of medial temporal lobe atrophy and white matter hyperintensities on magnetic resonance imaging. We found that a more inclusive approach identified individuals with a positive beta-amyloid-42 biomarker; a less inclusive approach captured individuals with higher medial temporal lobe atrophy; and a data-driven approach captured individuals with high white matter hyperintensities burden. The three approaches also captured some neuropsychological differences. We conclude that choice of approach may differ depending on the purpose. This study helps to advance our current understanding of the clinical and biological heterogeneity within SCI and MCI, particularly in the unselected memory clinic setting.

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.

Mild Cognitive Impairment: Diagnosis and Subtypes

Mild cognitive impairment (MCI) is a clinical diagnosis based on subjective cognitive decline, objective cognitive impairment, and relative preservation of activities of daily living. The diagnosis may be established via clinical interview, collateral history from an informant, and psychometric examination. Various consensus groups have proposed criteria for MCI in Alzheimer's disease (AD), Parkinson's disease, dementia with Lewy bodies, and vascular cognitive impairment. These diagnostic criteria have subtle but important differences. Criteria for subjective decline vary according to whether memory is impaired or whether impairment in any cognitive domain is sufficient. There are also differences with respect to whether the subjective decline is noted by the patient, a carer, or a clinician. The precise thresholds for classifying objective cognitive impairment also vary between various diagnostic criteria. There are also differences in the description of functional abilities. Once established, the diagnosis of MCI may be refined to 1 of 4 subtypes based on the pattern of cognitive impairment. The 4 subtypes are defined according to whether or not memory is impaired and whether 1 or more cognitive domains are impaired. Once a diagnosis of MCI has been made, the patient and the family should be counseled about social and legal implications as well as strategies for reducing the risk of progression to dementia. The main utilities of MCI as a nosology are to understand the natural history of neurodegenerative disorders such as AD, to identify those at increased risk of progressing to develop dementia, and to identifying individuals for putative treatments.

Signatures of Neuropsychological Test Results in the Long Life Family Study: A Cluster Analysis

BACKGROUND

Discovering patterns of cognitive domains and characterizing how these patterns associate with other risk factors and biomarkers can improve our understanding of the determinants of cognitive aging.

OBJECTIVE

To discover patterns of cognitive domains using neuropsychological test results in Long Life Family Study (LLFS) and characterize how these patterns associate with aging markers.

METHODS

5,086 LLFS participants were administered neuropsychological tests at enrollment. We performed a cluster analysis of six baseline neuropsychological test scores and tested the association between the identified clusters and various clinical variables, biomarkers, and polygenic risk scores using generalized estimating equations and the Chi-square test. We used Cox regression to correlate the clusters with the hazard of various medical events. We investigated whether the cluster information could enhance the prediction of cognitive decline using Bayesian beta regression.

RESULTS

We identified 12 clusters with different cognitive signatures that represent profiles of performance across multiple neuropsychological tests. These signatures significantly correlated with 26 variables including polygenic risk scores, physical and pulmonary functions, and blood biomarkers and were associated with the hazard of mortality (p < 0.01), cardiovascular disease (p = 0.03), dementia (p = 0.01), and skin cancer (p = 0.03).

CONCLUSION

The identified cognitive signatures capture multiple domains simultaneously and provide a holistic vision of cognitive function, showing that different patterns of cognitive function can coexist in aging individuals. Such patterns can be used for clinical intervention and primary care.

A latent class analysis of cognitive decline in US adults, BRFSS 2015-2020

BACKGROUND

Cognitive decline can be an early indicator for dementia. Using quantitative methods and national representative survey data, we can monitor the potential burden of disease at the population-level.

METHODS

BRFSS is an annual, nationally representative questionnaire in the United States. The optional cognitive decline module is a six-item self-reported scale pertaining to challenges in daily life due to memory loss and growing confusion over the past twelve months. Respondents are 45+, pooled from 2015-2020. Latent class analysis was used to determine unobserved subgroups of subjective cognitive decline (SCD) based on item response patterns. Multinomial logistic regression predicted latent class membership from socio-demographic covariates.

RESULTS

A total of 54,771 reported experiencing SCD. The optimal number of latent classes was three, labeled as Mild, Moderate, and Severe SCD. Thirty-five percent of the sample belonged to the Severe group. Members of this subgroup were significantly less likely to be older (65+ vs. 45-54 OR = 0.29, 95% CI: 0.23-0.35) and more likely to be non-Hispanic Black (OR = 1.80, 95% CI: 1.53-2.11), have not graduated high school (OR = 1.60, 95% CI: 1.34-1.91), or earned <$15K a year (OR = 3.03, 95% CI: 2.43-3.77).

CONCLUSIONS

This study determined three latent subgroups indicating severity of SCD and identified socio-demographic predictors. Using a single categorical indicator of SCD severity instead of six separate items improves the versatility of population-level surveillance.

The association between head motion during functional magnetic resonance imaging and executive functioning in older adults

Minimizing head motion during functional magnetic resonance imaging (fMRI) is important for maintaining the integrity of neuroimaging data. While there are a variety of techniques to control for head motion, oftentimes, individuals with excessive in-scanner motion are removed from analyses. Movement in the scanner tends to increase with age; however, the cognitive profile of these "high-movers" in older adults has yet to be explored. This study aimed to assess the association between in-scanner head motion (i.e., number of "invalid scans" flagged as motion outliers) and cognitive functioning (e.g., executive functioning, processing speed, and verbal memory performance) in a sample of 282 healthy older adults. Spearman's Rank-Order correlations showed that a higher number of invalid scans was significantly associated with poorer performance on tasks of inhibition and cognitive flexibility and with older age. Since performance in these domains tend to decline as a part of the non-pathological aging process, these findings raise concerns regarding the potential systematic exclusion due to motion of older adults with lower executive functioning in neuroimaging samples. Future research should continue to explore prospective motion correction techniques to better ensure the collection of quality neuroimaging data without excluding informative participants from the sample.

Decreased Electroencephalography Global Field Synchronization in Slow-Frequency Bands Characterizes Synaptic Dysfunction in Amnestic Subtypes of Mild Cognitive Impairment

Background

Mild cognitive impairment (MCI) is highly prevalent in a memory clinic setting and is heterogeneous regarding its clinical presentation, underlying pathophysiology, and prognosis. The most prevalent subtypes are single-domain amnestic MCI (sd-aMCI), considered to be a prodromal phase of Alzheimer’s disease (AD), and multidomain amnestic MCI (md-aMCI), which is associated with multiple etiologies. Since synaptic loss and dysfunction are the closest pathoanatomical correlates of AD-related cognitive impairment, we aimed to characterize it in patients with sd-aMCI and md-aMCI by means of resting-state electroencephalography (EEG) global field power (GFP), global field synchronization (GFS), and novel cerebrospinal fluid (CSF) synaptic biomarkers.

Methods

We included 52 patients with sd-aMCI (66.9 ± 7.3 years, 52% women) and 30 with md-aMCI (63.1 ± 7.1 years, 53% women). All patients underwent a detailed clinical assessment, resting-state EEG recordings and quantitative analysis (GFP and GFS in delta, theta, alpha, and beta bands), and analysis of CSF biomarkers of synaptic dysfunction, neurodegeneration, and AD-related pathology. Cognitive subtyping was based on a comprehensive neuropsychological examination. The Mini-Mental State Examination (MMSE) was used as an estimation of global cognitive performance. EEG and CSF biomarkers were included in a multivariate model together with MMSE and demographic variables, to investigate differences between sd-aMCI and md-aMCI.

Results

Patients with sd-aMCI had higher CSF phosphorylated tau, total tau and neurogranin levels, and lower values in GFS delta and theta. No differences were observed in GFP. The multivariate model showed that the most important synaptic measures for group separation were GFS theta, followed by GFS delta, GFP theta, CSF neurogranin, and GFP beta.

Conclusion

Patients with sd-aMCI when compared with those with md-aMCI have a neurophysiological and biochemical profile of synaptic damage, neurodegeneration, and amyloid pathology closer to that described in patients with AD. The most prominent signature in sd-aMCI was a decreased global synchronization in slow-frequency bands indicating that functional connectivity in slow frequencies is more specifically related to early effects of AD-specific molecular pathology.

Association of Antihypertensives That Stimulate vs Inhibit Types 2 and 4 Angiotensin II Receptors With Cognitive Impairment

Importance

Use of antihypertensive medications that stimulate type 2 and 4 angiotensin II receptors, compared with those that do not stimulate these receptors, has been associated with a lower risk of dementia. However, this association with cognitive outcomes in hypertension trials, with blood pressure levels in the range of current guidelines, has not been evaluated.

Objective

To examine the association between use of exclusively antihypertensive medication regimens that stimulate vs inhibit type 2 and 4 angiotensin II receptors on mild cognitive impairment (MCI) or dementia.

Design, Setting, and Participants

This cohort study is a secondary analysis (April 2011 to July 2018) of participants in the randomized Systolic Blood Pressure Intervention Trial (SPRINT), which recruited individuals 50 years or older with hypertension and increased cardiovascular risk but without a history of diabetes, stroke, or dementia. Data analysis was conducted from March 16 to July 6, 2021.

Exposures

Prevalent use of angiotensin II receptor type 2 and 4-stimulating or -inhibiting antihypertensive medication regimens at the 6-month study visit.

Main Outcomes and Measures

The primary outcome was a composite of adjudicated amnestic MCI or probable dementia.

Results

Of the 8685 SPRINT participants who were prevalent users of antihypertensive medication regimens at the 6-month study visit (mean [SD] age, 67.7 [11.2] years; 5586 [64.3%] male; and 935 [10.8%] Hispanic, 2605 [30.0%] non-Hispanic Black, 4983 [57.4%] non-Hispanic White, and 162 [1.9%] who responded as other race or ethnicity), 2644 (30.4%) were users of exclusively stimulating, 1536 (17.7%) inhibiting, and 4505 (51.9%) mixed antihypertensive medication regimens. During a median of 4.8 years of follow-up (95% CI, 4.7-4.8 years), there were 45 vs 59 cases per 1000 person-years of amnestic MCI or probable dementia among prevalent users of regimens that contained exclusively stimulating vs inhibiting antihypertensive medications (hazard ratio [HR], 0.76; 95% CI, 0.66-0.87). When comparing stimulating-only vs inhibiting-only users, amnestic MCI occurred at rates of 40 vs 54 cases per 1000 person-years (HR, 0.74; 95% CI, 0.64-0.87) and probable dementia at rates of 8 vs 10 cases per 1000 person-years (HR, 0.80; 95% CI, 0.57-1.14). Negative control outcome analyses suggested the presence of residual confounding.

Conclusions and Relevance

In this secondary analysis of SPRINT, prevalent users of regimens that contain exclusively antihypertensive medications that stimulate vs inhibit type 2 and 4 angiotensin II receptors had lower rates of incident cognitive impairment. Residual confounding cannot be ruled out. If these results are replicated in randomized clinical trials, certain antihypertensive medications could be prioritized to prevent cognitive decline.

Early Alert of Elderly Cognitive Impairment using Temporal Streaming Clustering

more than 44 million people have been diagnosed with dementia worldwide, and this number is estimated to triple by next three decades. Given this increasing trend of older adults with cognitive impairment (CI; dementia and mild cognitive impairment) and its significant underdiagnosis, early identification of CI and understanding its progression is a critical step towards a better quality of life for the aging population. Early alert of individual health changes could facilitate better ways for clinicians to diagnose CI in its early stages and come up with more effective treatment plans. However, there is a lack of approaches to characterize patient health conditions accounting for temporal information in an unsupervised manner. Limited CI cases and its costly ascertainment in clinical settings also make unsupervised learning more promising in CI research. In this paper, a streaming clustering model was used to determine distinct patterns of older adults' health changes from their clinical visits in Mayo Clinic Study of Aging. The streaming clustering was also examined to study its ability to generate early alerts for potential incidents of CI. Our analysis demonstrated that temporal characteristics incorporated in a streaming clustering model has a promising potential to increase power in predicting CI.

The relationship between vascular endothelial growth factor (VEGF) and amnestic mild cognitive impairment among older adults living with HIV

Older people with HIV (PWH) experience increased risk of age-related neurodegenerative disorders and cognitive decline, such as amnestic mild cognitive impairment (aMCI). The objective of this study was to examine the relationship between aMCI and plasma VEGF biomarkers among older PWH. Data were collected at a university-based research center from 2011 to 2013. Participants were 67 antiretroviral therapy-treated, virally suppressed PWH. Participants completed comprehensive neurobehavioral and neuromedical evaluations. aMCI status was determined using adapted Jak/Bondi criteria, classifying participants as aMCI + if their performance was > 1 SD below the normative mean on at least two of four memory assessments. VEGF family plasma biomarkers (i.e., VEGF, VEGF-C, VEGF-D, and PIGF) were measured by immunoassay. Logistic regression models were conducted to determine whether VEGF biomarkers were associated with aMCI status. Participants were mostly non-Hispanic white (79%) men (85%) with a mean age of 57.7 years. Eighteen (26.9%) participants met criteria for aMCI. Among potential covariates, only antidepressant drug use differed by aMCI status, and was included as a covariate. VEGF-D was significantly lower in the aMCI + group compared to the aMCI - group. No other VEGF levels (VEGF, VEGF-C, PIGF) differed by aMCI classification (ps > .05). In a sample of antiretroviral therapy-treated, virally suppressed PWH, lower levels of VEGF-D were associated with aMCI status. Longitudinal analyses in a larger and more diverse sample are needed to support VEGF-D as a putative biological marker of aMCI in HIV.

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.

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.

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.

Aggregation of Abnormal Memory Scores and Risk of Incident Alzheimer's Disease Dementia: A Measure of Objective Memory Impairment in Amnestic Mild Cognitive Impairment

OBJECTIVES

The criteria for objective memory impairment in mild cognitive impairment (MCI) are vaguely defined. Aggregating the number of abnormal memory scores (NAMS) is one way to operationalise memory impairment, which we hypothesised would predict progression to Alzheimer's disease (AD) dementia.

METHODS

As part of the Australian Imaging, Biomarkers and Lifestyle Flagship Study of Ageing, 896 older adults who did not have dementia were administered a psychometric battery including three neuropsychological tests of memory, yielding 10 indices of memory. We calculated the number of memory scores corresponding to z ≤ -1.5 (i.e., NAMS) for each participant. Incident diagnosis of AD dementia was established by consensus of an expert panel after 3 years.

RESULTS

Of the 722 (80.6%) participants who were followed up, 54 (7.5%) developed AD dementia. There was a strong correlation between NAMS and probability of developing AD dementia (r = .91, p = .0003). Each abnormal memory score conferred an additional 9.8% risk of progressing to AD dementia. The area under the receiver operating characteristic curve for NAMS was 0.87 [95% confidence interval (CI) .81-.93, p < .01]. The odds ratio for NAMS was 1.67 (95% CI 1.40-2.01, p < .01) after correcting for age, sex, education, estimated intelligence quotient, subjective memory complaint, Mini-Mental State Exam (MMSE) score and apolipoprotein E ϵ4 status.

CONCLUSIONS

Aggregation of abnormal memory scores may be a useful way of operationalising objective memory impairment, predicting incident AD dementia and providing prognostic stratification for individuals with MCI.

Mild cognitive impairment: narrative review of taxonomies and systematic review of their prediction of incident Alzheimer's disease dementia

Early detection of Alzheimer's disease is vital for developing novel treatments. Attempts to identify the intermediate state between normal cognition and dementia have evolved over the past 50 years. Current taxonomies of mild cognitive impairment (MCI) may be criticised for their imprecise operationalisation. With the advent of biomarkers such as amyloid-beta positron emission tomography imaging in established Alzheimer's disease, much research has focused on establishing which factors predict progression from MCI to Alzheimer's disease dementia. In this review, we discuss the historical context of MCI before reviewing the literature of MCI subtypes and their risk of progression to Alzheimer's disease dementia. Finally, we summarise the literature and discuss limitations and weaknesses of how the construct is operationalised and implemented, before offering suggestions for development of the concept of MCI. We conclude that MCI must be empirically defined for the sake of its predictive validity to identify Alzheimer's disease before dementia develops.

Structural magnetic resonance imaging for the early diagnosis of dementia due to Alzheimer's disease in people with mild cognitive impairment

BACKGROUND

Mild cognitive impairment (MCI) due to Alzheimer's disease is the symptomatic predementia phase of Alzheimer's disease dementia, characterised by cognitive and functional impairment not severe enough to fulfil the criteria for dementia. In clinical samples, people with amnestic MCI are at high risk of developing Alzheimer's disease dementia, with annual rates of progression from MCI to Alzheimer's disease estimated at approximately 10% to 15% compared with the base incidence rates of Alzheimer's disease dementia of 1% to 2% per year.

OBJECTIVES

To assess the diagnostic accuracy of structural magnetic resonance imaging (MRI) for the early diagnosis of dementia due to Alzheimer's disease in people with MCI versus the clinical follow-up diagnosis of Alzheimer's disease dementia as a reference standard (delayed verification). To investigate sources of heterogeneity in accuracy, such as the use of qualitative visual assessment or quantitative volumetric measurements, including manual or automatic (MRI) techniques, or the length of follow-up, and age of participants. MRI was evaluated as an add-on test in addition to clinical diagnosis of MCI to improve early diagnosis of dementia due to Alzheimer's disease in people with MCI.

SEARCH METHODS

On 29 January 2019 we searched Cochrane Dementia and Cognitive Improvement's Specialised Register and the databases, MEDLINE, Embase, BIOSIS Previews, Science Citation Index, PsycINFO, and LILACS. We also searched the reference lists of all eligible studies identified by the electronic searches.

SELECTION CRITERIA

We considered cohort studies of any size that included prospectively recruited people of any age with a diagnosis of MCI. We included studies that compared the diagnostic test accuracy of baseline structural MRI versus the clinical follow-up diagnosis of Alzheimer's disease dementia (delayed verification). We did not exclude studies on the basis of length of follow-up. We included studies that used either qualitative visual assessment or quantitative volumetric measurements of MRI to detect atrophy in the whole brain or in specific brain regions, such as the hippocampus, medial temporal lobe, lateral ventricles, entorhinal cortex, medial temporal gyrus, lateral temporal lobe, amygdala, and cortical grey matter.

DATA COLLECTION AND ANALYSIS

Four teams of two review authors each independently reviewed titles and abstracts of articles identified by the search strategy. Two teams of two review authors each independently assessed the selected full-text articles for eligibility, extracted data and solved disagreements by consensus. Two review authors independently assessed the quality of studies using the QUADAS-2 tool. We used the hierarchical summary receiver operating characteristic (HSROC) model to fit summary ROC curves and to obtain overall measures of relative accuracy in subgroup analyses. We also used these models to obtain pooled estimates of sensitivity and specificity when sufficient data sets were available.

MAIN RESULTS

We included 33 studies, published from 1999 to 2019, with 3935 participants of whom 1341 (34%) progressed to Alzheimer's disease dementia and 2594 (66%) did not. Of the participants who did not progress to Alzheimer's disease dementia, 2561 (99%) remained stable MCI and 33 (1%) progressed to other types of dementia. The median proportion of women was 53% and the mean age of participants ranged from 63 to 87 years (median 73 years). The mean length of clinical follow-up ranged from 1 to 7.6 years (median 2 years). Most studies were of poor methodological quality due to risk of bias for participant selection or the index test, or both. Most of the included studies reported data on the volume of the total hippocampus (pooled mean sensitivity 0.73 (95% confidence interval (CI) 0.64 to 0.80); pooled mean specificity 0.71 (95% CI 0.65 to 0.77); 22 studies, 2209 participants). This evidence was of low certainty due to risk of bias and inconsistency. Seven studies reported data on the atrophy of the medial temporal lobe (mean sensitivity 0.64 (95% CI 0.53 to 0.73); mean specificity 0.65 (95% CI 0.51 to 0.76); 1077 participants) and five studies on the volume of the lateral ventricles (mean sensitivity 0.57 (95% CI 0.49 to 0.65); mean specificity 0.64 (95% CI 0.59 to 0.70); 1077 participants). This evidence was of moderate certainty due to risk of bias. Four studies with 529 participants analysed the volume of the total entorhinal cortex and four studies with 424 participants analysed the volume of the whole brain. We did not estimate pooled sensitivity and specificity for the volume of these two regions because available data were sparse and heterogeneous. We could not statistically evaluate the volumes of the lateral temporal lobe, amygdala, medial temporal gyrus, or cortical grey matter assessed in small individual studies. We found no evidence of a difference between studies in the accuracy of the total hippocampal volume with regards to duration of follow-up or age of participants, but the manual MRI technique was superior to automatic techniques in mixed (mostly indirect) comparisons. We did not assess the relative accuracy of the volumes of different brain regions measured by MRI because only indirect comparisons were available, studies were heterogeneous, and the overall accuracy of all regions was moderate.

AUTHORS' CONCLUSIONS

The volume of hippocampus or medial temporal lobe, the most studied brain regions, showed low sensitivity and specificity and did not qualify structural MRI as a stand-alone add-on test for an early diagnosis of dementia due to Alzheimer's disease in people with MCI. This is consistent with international guidelines, which recommend imaging to exclude non-degenerative or surgical causes of cognitive impairment and not to diagnose dementia due to Alzheimer's disease. In view of the low quality of most of the included studies, the findings of this review should be interpreted with caution. Future research should not focus on a single biomarker, but rather on combinations of biomarkers to improve an early diagnosis of Alzheimer's disease dementia.

Hierarchical Clustering Analyses of Plasma Proteins in Subjects With Cardiovascular Risk Factors Identify Informative Subsets Based on Differential Levels of Angiogenic and Inflammatory Biomarkers

Agglomerative hierarchical clustering analysis (HCA) is a commonly used unsupervised machine learning approach for identifying informative natural clusters of observations. HCA is performed by calculating a pairwise dissimilarity matrix and then clustering similar observations until all observations are grouped within a cluster. Verifying the empirical clusters produced by HCA is complex and not well studied in biomedical applications. Here, we demonstrate the comparability of a novel HCA technique with one that was used in previous biomedical applications while applying both techniques to plasma angiogenic (FGF, FLT, PIGF, Tie-2, VEGF, VEGF-D) and inflammatory (MMP1, MMP3, MMP9, IL8, TNFα) protein data to identify informative subsets of individuals. Study subjects were diagnosed with mild cognitive impairment due to cerebrovascular disease (MCI-CVD). Through comparison of the two HCA techniques, we were able to identify subsets of individuals, based on differences in VEGF (p < 0.001), MMP1 (p < 0.001), and IL8 (p < 0.001) levels. These profiles provide novel insights into angiogenic and inflammatory pathologies that may contribute to VCID.

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.

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.

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.

Prognostic Accuracy of Mild Cognitive Impairment Subtypes at Different Cut-Off Levels

BACKGROUND/AIMS

The prognostic accuracy of mild cognitive impairment (MCI) in clinical settings is debated, variable across criteria, cut-offs, subtypes, and follow-up time. We aimed to estimate the prognostic accuracy of MCI and the MCI subtypes for dementia using three different cut-off levels.

METHODS

Memory clinic patients were followed for 2 (n = 317, age 63.7 ± 7.8) and 4-6 (n = 168, age 62.6 ± 7.4) years. We used 2.0, 1.5, and 1.0 standard deviations (SD) below the mean of normal controls (n = 120, age 64.1 ± 6.6) to categorize MCI and the MCI subtypes. Prognostic accuracy for dementia syndrome at follow-up was estimated.

RESULTS

Amnestic multi-domain MCI (aMCI-md) significantly predicted dementia under all conditions, most markedly when speed/attention, language, or executive function was impaired alongside memory. For aMCI-md, sensitivity increased and specificity decreased when the cut-off was lowered from 2.0 to 1.5 and 1.0 SD. Non-subtyped MCI had a high sensitivity and a low specificity.

CONCLUSION

Our results suggest that aMCI-md is the only viable subtype for predicting dementia for both follow-up times. Lowering the cut-off decreases the positive predictive value and increases the negative predictive value of aMCI-md. The results are important for understanding the clinical prognostic utility of MCI, and MCI as a non-progressive disorder.

Cognitive Impairment Is Reflected by an Increased Difference between Real and Imagined Timed Up and Go Test Performance

BACKGROUND

Recent research suggests using an imaginary version of the Timed Up and Go test (TUG) for a first assessment of cognitive impairment. By using the time difference between a real (TUGr) and an imagined (TUGi) TUG task, the objective of this study was to examine the effect of cognitive impairment on motor imagery ability.

METHODS

Fifty-two participants (mean age 69.3 ± 4.0 years) with mild cognitive impairment or subjective cognitive impairment were included in this study. The time difference between the TUGr and the TUGi was used as the main outcome. The Trail Making Test part B (TMT B), the ratio between TMT A and TMT B, and the Montreal Cognitive Assessment (MoCA) battery were the main independent variables.

RESULTS

The difference between TUGr and TUGi performance time and the TMT B performance time increased with decreasing cognitive function (p < 0.01). There was no relationship between TUGr and TUGi performance time and TMT B/A ratio. There were significant correlations between TUG time differences and the MoCA score (r = -0.489, p < 0.01), the TMT B (r = 0.364, p < 0.01), and the TMT B/A ratio (r = 0.377, p < 0.01).

CONCLUSION

The combination of TUGr and TUGi may have added value in assessing cognitive impairment, which is a possible pre-stage of dementia.

Neurocognitive Deficits and Effects of Cognitive Reserve in Mild Cognitive Impairment

BACKGROUND/AIMS

Mild cognitive impairment (MCI) is a frequent syndrome in the older population, which involves an increased risk to develop Alzheimer's disease (AD). The latter can be modified by the cognitive reserve, which can be operationalized by the length of school education. MCI can be differentiated into four subtypes according to the cognitive domains involved: amnestic MCI, multiple-domain amnestic MCI, non-amnestic MCI and multiple-domain non-amnestic MCI. While neurocognitive deficits are a constituent of the diagnosis of these subtypes, the question of how they refer to the cognitive reserve still needs to be clarified.

METHODS

We examined neuropsychological deficits in healthy controls, patients with MCI and patients with mild AD (n = 485) derived from a memory clinic. To reduce the number of neuropsychological variables, a factor analysis with varimax rotation was calculated. In a second step, diagnostic groups including MCI subtypes were compared with respect to their clinical and neuropsychological characteristics including cognitive reserve.

RESULTS

Most MCI patients showed the amnestic multiple-domain subtype followed by the pure amnestic subtype, while the non-amnestic subtypes were rare. The amnestic subtype displayed a significantly higher level of cognitive reserve and higher MMSE scores than the amnestic multiple-domain subtype, which was in most cases characterized by additional psychomotor and executive deficits.

CONCLUSIONS

These findings confirm earlier reports revealing that the amnestic multiple-domain subtype is the most frequent one and indicating that a high cognitive reserve may primarily prevent psychomotor and executive deficits in MCI.

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.

Comparison Between an Empirically Derived and a Standard Classification of Amnestic Mild Cognitive Impairment From a Sample Of Adults With Subjective Cognitive Complaints

Objective: The aim of this study is to compare an empirically derived classification of amnestic mild cognitive impairment (aMCI) from a sample of adults with subjective cognitive complaints by using cluster analysis of their performance on the California Verbal Learning Test (CVLT) with a classification of aMCI based on standard clinical criteria. Method: Three hundred ninety-one individuals aged 48 years and older were diagnosed as aMCI or healthy controls. Cluster analysis of the CVLT performance was conducted, followed by logistic regression analysis. Results: A two-cluster solution performed on the CVLT measures correctly classified 98.0% of the aMCI patients and 73.4% of the healthy controls diagnosed by using standard aMCI criteria. Discussion: The empirically derived classification of aMCI is consistent with the classification based on standard criteria; however, standard criteria should also be considered to prevent false positives.

Amyloid and Tau Biomarkers in Subjective Cognitive Impairment

Subjective cognitive impairment (SCI) refers to concerns regarding one's cognitive functioning in the absence of objective evidence of impairment, and may represent an early stage of Alzheimer's disease. However, as not all individuals with SCI cognitively decline, there is growing interest in the early identification of those individuals with SCI who are most at risk of developing Alzheimer's disease. One promising method of early identification involves the use of biomarkers that are known to be associated with the pathophysiology of the disease; in particular, markers of amyloid and tau accumulation. While there has been substantial research on amyloid and tau biomarkers in the context of mild cognitive impairment (MCI), only recently has attention shifted to SCI, which may represent an even earlier stage in the disease course. The purpose of this paper is to qualitatively review the literature on amyloid and tau biomarkers in SCI. A brief discussion of non-amyloid/tau biomarkers is also included. Not surprisingly, we found that amyloid and tau biomarker profiles become increasingly abnormal from SCI, to MCI, to Alzheimer's disease. Additionally, although amyloid and tau biomarkers appear to be unable to differentiate between SCI and healthy controls, there is some evidence to suggest that they may be able to differentiate between those individuals with SCI who cognitively decline over time and those who do not. While this finding has potential clinical implications, achieving optimal predictive value will likely require further research into the use of numerous biomarkers in combination.

Olfactory Dysfunction, Olfactory Bulb Volume and Alzheimer's Disease: Is There a Correlation? A Pilot Study1

BACKGROUND

Olfactory dysfunction is present since the earliest stage of Alzheimer's disease (AD). In AD patients, the olfactory impairment has been correlated with atrophy of some structures of the olfactory system, but the role of the olfactory bulb remains unclear.

OBJECTIVE

The aim of our work is to test if patients suffering from AD exhibit a statistically significant reduction of the average volume of the olfactory bulb (OBV) compared to healthy subjects.

METHODS

78 subjects were enrolled in the study and divided into three groups: 28 healthy elderly (22 females, 6 males, mean age 69.4 ± 9.2), 25 patients with mild cognitive impairment (MCI) amnestic type (14 females, 11 males, mean age 74.5 ± 7.5), and 25 mild AD patients (14 females, 11 males, mean age 73.7 ± 6.8). Every subject underwent an MRI study of the olfactory bulb and an olfactory assessment with the Sniffin' Stick Extended Test.

RESULTS

The statistical analysis showed no correlation between the OBV and MCI or AD. Moreover, olfactory function and OBV were not correlated in any of the three groups.

CONCLUSION

The reduction of OBV does not seem to represent an index of neuronal damage in the earliest stages of AD.

Risk for Mild Cognitive Impairment Is Associated With Semantic Integration Deficits in Sentence Processing and Memory

OBJECTIVES

We examined the degree to which online sentence processing and offline sentence memory differed among older adults who showed risk for amnestic and nonamnestic varieties of mild cognitive impairment (MCI), based on psychometric classification.

METHOD

Participants (N = 439) read a series of sentences in a self-paced word-by-word reading paradigm for subsequent recall and completed a standardized cognitive test battery. Participants were classified into 3 groups: unimpaired controls (N = 281), amnestic MCI (N = 94), or nonamnestic MCI (N = 64).

RESULTS

Relative to controls, both MCI groups had poorer sentence memory and showed reduced sentence wrap-up effects, indicating reduced allocation to semantic integration processes. Wrap-up effects predicted subsequent recall in the control and nonamnestic groups. The amnestic MCI group showed poorer recall than the nonamnestic MCI group, and only the amnestic MCI group showed no relationship between sentence wrap-up and recall.

DISCUSSION

Our findings suggest that psychometrically defined sub-types of MCI are associated with unique deficits in sentence processing and can differentiate between the engagement of attentional resources during reading and the effectiveness of engaging attentional resources in producing improved memory.

The identification of cognitive subtypes in Alzheimer's disease dementia using latent class analysis

OBJECTIVE

Alzheimer's disease (AD) is a heterogeneous disorder with complex underlying neuropathology that is still not completely understood. For better understanding of this heterogeneity, we aimed to identify cognitive subtypes using latent class analysis (LCA) in a large sample of patients with AD dementia. In addition, we explored the relationship between the identified cognitive subtypes, and their demographical and neurobiological characteristics.

METHODS

We performed LCA based on neuropsychological test results of 938 consecutive probable patients with AD dementia using Mini-Mental State Examination as the covariate. Subsequently, we performed multinomial logistic regression analysis with cluster membership as dependent variable and dichotomised demographics, APOE genotype, cerebrospinal fluid biomarkers and MRI characteristics as independent variables.

RESULTS

LCA revealed eight clusters characterised by distinct cognitive profile and disease severity. Memory-impaired clusters-mild-memory (MILD-MEM) and moderate-memory (MOD-MEM)-included 43% of patients. Memory-spared clusters mild-visuospatial-language (MILD-VILA), mild-executive (MILD-EXE) and moderate-visuospatial (MOD-VISP) -included 29% of patients. Memory-indifferent clusters mild-diffuse (MILD-DIFF), moderate-language (MOD-LAN) and severe-diffuse (SEV-DIFF) -included 28% of patients. Cognitive clusters were associated with distinct demographical and neurobiological characteristics. In particular, the memory-spared MOD-VISP cluster was associated with younger age, APOE e4 negative genotype and prominent atrophy of the posterior cortex.

CONCLUSIONS

Using LCA, we identified eight distinct cognitive subtypes in a large sample of patients with AD dementia. Cognitive clusters were associated with distinct demographical and neurobiological characteristics.

Alzheimer's disease--subcortical vascular disease spectrum in a hospital-based setting: Overview of results from the Gothenburg MCI and dementia studies

The ability to discriminate between Alzheimer's disease (AD), subcortical vascular disease, and other cognitive disorders is crucial for diagnostic purposes and clinical trial outcomes. Patients with primarily subcortical vascular disease are unlikely to benefit from treatments targeting the AD pathogenic mechanisms and vice versa. The Gothenburg mild cognitive impairment (MCI) and dementia studies are prospective, observational, single-center cohort studies suitable for both cross-sectional and longitudinal analysis that outline the cognitive profiles and biomarker characteristics of patients with AD, subcortical vascular disease, and other cognitive disorders. The studies, the first of which started in 1987, comprise inpatients with manifest dementia and patients seeking care for cognitive disorders at an outpatient memory clinic. This article gives an overview of the major published papers (neuropsychological, imaging/physiology, and neurochemical) of the studies including the ongoing Gothenburg MCI study. The main findings suggest that subcortical vascular disease with or without dementia exhibit a characteristic neuropsychological pattern of mental slowness and executive dysfunction and neurochemical deviations typical of white matter changes and disturbed blood-brain barrier function. Our findings may contribute to better healthcare for this underrecognized group of patients. The Gothenburg MCI study has also published papers on multimodal prediction of dementia, and cognitive reserve.

Detection of Motor Changes in Huntington's Disease Using Dynamic Causal Modeling

Deficits in motor functioning are one of the hallmarks of Huntington's disease (HD), a genetically caused neurodegenerative disorder. We applied functional magnetic resonance imaging (fMRI) and dynamic causal modeling (DCM) to assess changes that occur with disease progression in the neural circuitry of key areas associated with executive and cognitive aspects of motor control. Seventy-seven healthy controls, 62 pre-symptomatic HD gene carriers (preHD), and 16 patients with manifest HD symptoms (earlyHD) performed a motor finger-tapping fMRI task with systematically varying speed and complexity. DCM was used to assess the causal interactions among seven pre-defined regions of interest, comprising primary motor cortex, supplementary motor area (SMA), dorsal premotor cortex, and superior parietal cortex. To capture heterogeneity among HD gene carriers, DCM parameters were entered into a hierarchical cluster analysis using Ward's method and squared Euclidian distance as a measure of similarity. After applying Bonferroni correction for the number of tests, DCM analysis revealed a group difference that was not present in the conventional fMRI analysis. We found an inhibitory effect of complexity on the connection from parietal to premotor areas in preHD, which became excitatory in earlyHD and correlated with putamen atrophy. While speed of finger movements did not modulate the connection from caudal to pre-SMA in controls and preHD, this connection became strongly negative in earlyHD. This second effect did not survive correction for multiple comparisons. Hierarchical clustering separated the gene mutation carriers into three clusters that also differed significantly between these two connections and thereby confirmed their relevance. DCM proved useful in identifying group differences that would have remained undetected by standard analyses and may aid in the investigation of between-subject heterogeneity.

Elevated rates of mild cognitive impairment in HIV disease

With the rising number of individuals in their 50s and 60s who are infected with HIV, concerns have emerged about possible increases in the rates of non-HIV-associated dementias. The current study examined the prevalence of mild cognitive impairment (MCI) in older HIV-infected adults, since MCI is an intermediate state between typical cognitive aging and dementia that emerges in this age range. Participants included 75 adults with HIV disease aged 50 years and older who were on combination antiretroviral therapy (cART) and had undetectable plasma viral loads and 80 demographically similar HIV-seronegative comparison subjects. Participants completed a research neuropsychological evaluation that was used to classify MCI according to the comprehensive diagnostic scheme described by Bondi et al. (J Alzheimers Dis 42:275-289, 2014). HIV-infected persons were over seven times more likely to have an MCI designation (16 %) than their seronegative counterparts (2.5 %). Within the HIV+ cohort, MCI had minimal overlap with diagnoses of asymptomatic neurocognitive impairment and was significantly associated with older age, lower Karnofsky Scale of Performance Scores, and mild difficulties performing instrumental activities of daily living (iADLs). HIV infection in older adults is associated with a notably elevated concurrent risk of MCI, which may increase the likelihood of developing non-HIV-associated dementias as this population ages further.

Atrophy of presubiculum and subiculum is the earliest hippocampal anatomical marker of Alzheimer's disease

BACKGROUND

There is no consensus about which hippocampal subfields become atrophic earliest in the course of Alzheimer's disease (AD).

METHODS

Thirty AD patients, 41 mild cognitive impairment (MCI) patients, and 38 healthy controls (HCs) underwent cerebral magnetic resonance imaging (with an automated segmentation protocol for the volumetric analysis of hippocampal subfields) and a test of immediate and delayed recall of a 15-word list.

RESULTS

The volumes of the presubiculum and subiculum presented the most remarkable reduction in the patient's groups. In the MCI group, only the volumes of presubiculum and subiculum predicted performance on the memory tests. In AD patients, the volumes of all hippocampal subfields (with the notable exception of the CA1) predicted memory scores.

CONCLUSIONS

Our data point to a prevalent atrophy of the presubicular-subicular complex from the early phases of AD. This finding is consistent with neuropathological observations in AD patients and probably reflects the severe degeneration of the perforant pathway while penetrating the hippocampus through the subicular field in its course from the entorhinal cortex to the dentate gyrus.