Heterogeneity in mild cognitive impairment: differences in neuropsychological profile and associated white matter lesion pathology

Neurocognitive clusters: A pilot study of young people with affective disorders in an inpatient facility

BACKGROUND

There is growing evidence to support the need for personalised intervention in the early stages of a major psychiatric illness, as well as the clear delineation of subgroups in psychiatric disorders based on cognitive impairment. Affective disorders are often accompanied by neurocognitive deficits; however a lack of research among young adult inpatients highlights the need to assess the utility of cognitive testing in this population.

METHODS

A computerised cognitive battery was administered to 50 current inpatient young adults (16-30 years; 75% female) with an affective disorder. Patients also completed a computerised self-report questionnaire (to measure demographics and clinical features) that included items evaluating subjective impressions of their cognition.

RESULTS

Hierarchical cluster analysis determined two neurocognitive subgroups: cluster 1 (n = 16) showed more severe impairments in sustained attention and memory as well as higher anxiety levels, compared to their peers in cluster 2 (n = 30) who showed the most impaired attentional switching. Across the sample, poor sustained attention was significantly correlated with higher levels of current anxiety and depressive symptoms, whereas poor verbal memory was significantly associated with increased psychological distress.

LIMITATIONS

This study has a relatively small sample size (due to it being a pilot/feasibility study). Furthermore, future studies should aim to assess inpatient samples compared to community care samples, as well as healthy controls, on a larger scale.

CONCLUSIONS

The findings suggest neurocognitive profiles are important in understanding phenotypes within young people with severe affective disorders. With clear subgroups based on cognitive impairment being demonstrated, the clinical utility and use of new and emerging technologies is warranted in such inpatients facilities. This pilot/feasibility study has strengthened the utility of cognitive screening as standard clinical care in an inpatient unit.

Parcellating cognitive heterogeneity in early psychosis-spectrum illnesses: A cluster analysis

Cognitive impairment is argued to represent a core feature of psychosis-spectrum illnesses. However, within-diagnosis heterogeneity is common, and risk factors for poor cognition remain to be examined after statistically accounting for heterogeneity. Accordingly, we used a data-driven technique (cluster analysis) to empirically-derive cognitive clusters across diagnoses and examined whether concurrent substance use or a history of a neurodevelopmental/behavioral disorder differed between clusters. Data from 135 young help-seekers (aged 12-30 years) with a psychosis-spectrum illness were retrospectively analyzed. Ward's hierarchical cluster analysis classified three cognitive clusters characterized by: (1) normal-range; (2) mixed; and (3) grossly-impaired performance. Despite mostly comparable clinical and demographic measures, cluster 1 had superior socio-occupational functioning and the highest estimated premorbid IQ, followed sequentially by clusters 2 and 3. Proportions of cannabis and amphetamine users did not differ significantly across clusters, nor did rates of patients with a neurodevelopmental/behavioral disorder history. Cluster 3 was however comprised of fewer 'risky' drinkers, possibly reflecting reduced opportunity for social drinking associated with cognitive impairment. Estimated premorbid IQ predicted cluster membership (2 vs. 1 & 3 vs. 1), as did clinician-rated socio-occupational functioning and 'not being enrolled in school or tertiary education' (3 vs. 1). Our results suggest that concurrent substance use and history of a neurodevelopmental/behavioral disorder do not adequately explain cluster-level cognitive variance in this sample. Future work should integrate neurobiological measures associated with cognition (e.g. white matter integrity) to discern whether clusters reflect neurobiological subtypes better representative of pathophysiology than present symptom-based classifications.

Examining differences in neuropsychiatric symptom factor trajectories in empirically derived mild cognitive impairment subtypes

OBJECTIVE

The aim of this study was to examine neuropsychiatric symptom (NPS) factor severity progression over time in empirically derived (ED) mild cognitive impairment (MCI) subtypes.

METHODS

Participants in the Alzheimer's Disease Neuroimaging Initiative study diagnosed with MCI by Alzheimer's Disease Neuroimaging Initiative protocol using conventional clinical (CC) criteria (n = 788) were reclassified using cluster analysis as amnestic, dysnomic, dysexecutive MCI, or cluster-derived normal (CC-Normal) using empirical criteria. Cognitively normal (CN) participants (n = 207) were also identified. The Neuropsychiatric Inventory-Questionnaire (NPI-Q) was administered from baseline through 48-month follow-up. Exploratory factor analysis was completed to determine the NPI-Q factor structure at 6-month follow-up. Multilevel modeling was used to determine NPI-Q symptom severity factor and apathy symptom progression over time by cognitive subtype.

RESULTS

The exploratory factor analysis revealed that the NPI-Q consisted of 2 factors: hyperactivity/agitation and mood symptoms. Using clinical and empirical criteria, all MCI groups were identified as having more severe hyperactivity/agitation symptoms than CN participants. However, only the amnestic MCI group identified using empirical criteria showed an increase in symptom severity over time relative to CN participants. Mood factor and apathy symptoms were found to be more severe in dysexecutive and amnestic groups in both models. Similarly, both models identified a significant worsening of mood and apathy symptoms over time for dysexecutive and amnestic groups relative to CN participants.

CONCLUSIONS

This study provides further support that empirical criteria aid in examining the progression of clinical characteristics associated with MCI. Further, it helps to identify which MCI subtypes may be at higher risk for NPS progression.

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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).

Effects of white matter lesions on brain perfusion in patients with mild cognitive impairment

OBJECTIVE

To evaluate the effects of white matter lesions on regional cerebral blood flow in subjects with amnestic mild cognitive impairment.

PATIENTS AND METHODS

Seventy-five subjects with mild cognitive impairment (36 men and 39 women; mean age, 78.1 years) were included in the study. We used the Mini-Mental State Examination to assess cognitive function. All subjects underwent brain magnetic resonance imaging and ^99mTc ethylcysteinate dimer single photon emission computed tomography. Subjects were stratified based on the presence or absence of white matter lesions on magnetic resonance imaging. Statistical parametric mapping of differences in regional cerebral blood flow between the two groups were assessed by voxel-by-voxel group analysis using SPM8.

RESULTS

Of all 75 subjects with mild cognitive impairment, 46 (61.3%) had mild to moderate white matter lesions. The prevalence of hypertension tended to be higher in subjects with white matter lesions than in those without white matter lesions. Mini-Mental State Examination scores were significantly lower in subjects with white matter lesions than in those without white matter lesions. Subjects with white matter lesions had decreased regional cerebral blood flow mainly in the frontal, parietal, and medial temporal lobes, as well as the putamen, compared to those without white matter lesions.

CONCLUSION

In subjects with mild cognitive impairment, white matter lesions were associated with cognitive impairment and mainly frontal lobe brain function.

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).

Can a tablet-based cancellation test identify cognitive impairment in older adults?

Background and objective

There has been a growing interest in using computerized cognitive assessment to detect age-related cognitive disorders. We have developed a tablet-based cancellation test (e-CT), previously shown as a reliable measure of executive functions and free of effect of familiarity with computer-based devices in healthy older adults. This study aimed to investigate the influence of demographics and current daily use of computer-based devices in older adults with Mild Cognitive Impairment (MCI) and Alzheimer’s disease (AD). We further studied the ability of the e-CT to discriminate MCI and AD patients from older adults with normal cognition (NC).

Methods

The e-CT was administered to 325 older adults (NC = 112, MCI = 129, AD = 84). Subjects also performed the K-T test, a paper-and-pencil cancellation test from which the e-CT was developed. Multiple linear regression analyses were conducted to assess the contribution of demographics and current daily use of computer-based devices on the e-CT in patient groups. The Receiver Operating Characteristic (ROC) curves and the Area Under the Curve (AUC) were established to compare the efficacy of the e-CT and the K-T test to classify subjects into diagnostic groups.

Results

In the MCI group, age (B = -0.37, p<0.001) and current daily use of computer-based devices (B = 5.85, p<0.001) were associated with the number of correct cancellations of the e-CT. In the AD group, only current daily use of a computer-based device was a significant contributor (B = 6.28, p<0.001). The e-CT (AUC = 0.811; 95% confidence interval [CI]: 0.756–0.867) and the K-T (AUC = 0.837; CI: 0.787–0.887) showed good and comparable diagnostic accuracy to discriminate between MCI and NC subjects. To discriminate between NC and AD, both tests showed high diagnostic accuracy, with the AUC values of 0.923 (CI: 0.876–0.971) and 0.929 (95%CI: 0.886–0.972) for the e-CT and the K-T, respectively.

Conclusion

The e-CT presents satisfying discriminative validity and is a promising tool for detection of early cognitive impairment in older adults.

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.

A quantitative meta-analysis of olfactory dysfunction in mild cognitive impairment

BACKGROUND

The connection between Alzheimer's disease (AD) and olfactory deficits is well documented and further, alterations in olfactory functioning may signal declines in functions associated with dementia. The aim of the present comprehensive meta-analysis was to investigate the nature of olfactory deficits in mild cognitive impairment (MCI).

METHODS

Articles were identified through computerised literature search from inception to 30 June 2016 using PubMed, MEDLINE and PsychInfo databases. In order to control for differences in sample size during effect size computation, studies were weighted according to their inverse variance estimates.

RESULTS

31 articles (62 effects) were identified, which included 1993 MCI patients and 2861 healthy older adults (HOA). Included studies contrasted odour identification, discrimination, detection threshold and/or memory between cases and controls. Moderate to large and heterogeneous effects were seen for olfactory deficits in MCI relative to HOA (d=-0.76, 95% CI -0.87<δ<-0.64). Moderator analysis revealed that tests of odour identification yielded larger effect sizes than those of odour detection threshold or memory. In addition, a potential interaction between age and sex was observed, with male patients carrying a larger burden of olfactory deficit and older female patients performing better on olfactory tests.

CONCLUSIONS AND RELEVANCE

Olfactory deficits are present and robust in MCI. Odour identification is most impaired in MCI, which parallels the most prominent sensory deficit seen in AD. As such, a simple-to-administer test of odour identification warrants inclusion in the screening of individuals at risk for developing AD.

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.

Apathy and intrinsic functional connectivity networks in amnestic mild cognitive impairment

BACKGROUND

Although several prior works reported that apathy is associated with conversion to Alzheimer's disease in individuals with amnestic mild cognitive impairment (aMCI), effects of apathy on the functional connectivity (FC) of the brain remain unclear. In this study, we assessed the pattern of association between apathy and default mode network (DMN), salience network and central executive network (CEN) in aMCI subjects.

METHODS

Fifty subjects with aMCI and 50 controls (CONs) participated in this study. They underwent clinical assessments and magnetic resonance imaging for the structural and resting-state scan. We explored the patterns of association between apathy inventory (IA) total score and the whole-brain voxel-wise FCs of the DMN, salience network and CEN in aMCI subjects.

RESULTS

We observed that the FCs of the DMN were less and those of CEN were more in the aMCI group than the CON group. Total IA score was negatively correlated with FCs of the anterior cingulate within the DMN, and positively correlated with FCs of the middle frontal, inferior frontal, and supramarginal gyrus within the CEN in the aMCI group.

CONCLUSION

Our findings suggest that distinctive patterns of association between apathy and FCs in the DMN and CEN in the aMCI group might reflect the putative role of functional network change in the development of apathy in aMCI.

Mild cognitive impairment (MCI) in long-term care patients: subtype classification and occurrence

OBJECTIVES

This study examines mild cognitive impairment (MCI) in long-term care settings by identifying and quantifying MCI subtypes in a combined sample of nursing home and assisted-living patients. We compared impairment thresholds of 1-SD and 1.5-SD to determine if different cut-offs differentially affect occurrence rates.

METHOD

One hundred and eight participants who met general criteria for MCI were included for the purposes of this study. The general diagnosis of MCI was based on criteria. Participants were further grouped into MCI subtypes. Based on previously established norms, Brief Cognitive Assessment Tool (BCAT) factor scores were used to assess whether MCI participants met either the 1-SD and 1.5-SD impairment thresholds for memory, executive functions, and attentional capacity.

RESULTS

Using both 1-SD and 1.5-SD impairment thresholds, three clear MCI subtypes were identified: amnestic, single-domain; non-amnestic, single-domain (executive); and amnestic, multi-domain (memory and executive). A fourth category (undifferentiated) was identified in patients who did not meet criteria for a distinct MCI subtype, but still had cognitive impairments. The stricter impairment threshold of 1.5-SD resulted in fewer patients classified as having any of the three domain-specific subtypes.

CONCLUSION

Based on a sample of nursing home and assisted-living patients, we identified three MCI subtypes, and a fourth category consisting of participants with general MCI, but without clear evidence of domain-specific cognitive impairment. When selecting impairment thresholds, one should consider the impact on the identification of MCI subtypes and the probability of misdiagnoses.

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

OBJECTIVE

We investigated differences in regional cortical thickness between previously identified empirically derived mild cognitive impairment (MCI) subtypes (amnestic MCI, dysnomic MCI, dysexecutive/mixed MCI, and cluster-derived normal) in order to determine whether these cognitive subtypes would show different patterns of cortical atrophy.

METHODS

Participants were 485 individuals diagnosed with MCI and 178 cognitively normal individuals from the Alzheimer's Disease Neuroimaging Initiative. Cortical thickness estimates were computed for 32 regions of interest per hemisphere. Statistical group maps compared each MCI subtype to cognitively normal participants and to one another.

RESULTS

The pattern of cortical thinning observed in each MCI subtype corresponded to their cognitive profile. No differences in cortical thickness were found between the cluster-derived normal MCI subtype and the cognitively normal group. Direct comparison between MCI subtypes suggested that the cortical thickness patterns reflect increasing disease severity.

CONCLUSIONS

There is an ordered pattern of cortical atrophy among patients with MCI that coincides with their profiles of increasing cognitive dysfunction. This heterogeneity is not captured when patients are grouped by conventional diagnostic criteria. Results in the cluster-derived normal group further support the premise that the conventional MCI diagnostic criteria are highly susceptible to false-positive diagnostic errors. Findings suggest a need to (1) improve the diagnostic criteria by reducing reliance on conventional screening measures, rating scales, and a single memory measure in order to avoid false-positive errors; and (2) divide MCI samples into meaningful subgroups based on cognitive and biomarkers profiles-a method that may provide better staging of MCI and inform prognosis.

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.

Subtle Cognitive Decline and Biomarker Staging in Preclinical Alzheimer's Disease

The NIA-AA criteria for "preclinical" Alzheimer's disease (AD) propose a staging method in which AD biomarkers follow an invariable temporal sequence in accordance with the amyloid cascade hypothesis. However, recent findings do not align with the proposed temporal sequence and "subtle cognitive decline," which has not been definitively operationalized, may occur earlier than suggested in preclinical AD. We aimed to define "subtle cognitive decline" using sensitive and reliable neuropsychological tests, and to examine the number and sequence of biomarker abnormalities in the Alzheimer's Disease Neuroimaging Initiative (ADNI). 570 cognitively normal ADNI participants were classified based on NIA-AA criteria and separately based on the number of abnormal biomarkers/cognitive markers associated with preclinical AD that each individual possessed. Results revealed that neurodegeneration alone was 2.5 times more common than amyloidosis alone at baseline. For those who demonstrated only one abnormal biomarker at baseline and later progressed to mild cognitive impairment/AD, neurodegeneration alone was most common, followed by amyloidosis alone or subtle cognitive decline alone, which were equally common. Findings suggest that most individuals do not follow the temporal order proposed by NIA-AA criteria. We provide an operational definition of subtle cognitive decline that captures both cognitive and functional decline. Additionally, we offer a new approach for staging preclinical AD based on number of abnormal biomarkers, without regard to their temporal order of occurrence. This method of characterizing preclinical AD is more parsimonious than the NIA-AA staging system and does not presume that all patients follow a singular invariant expression of the disease.

Standardization, Clinical Validation, and Typicality Norms of a New Test Assessing Semantic Verbal Fluency

OBJECTIVE

Semantic verbal fluency (SVF) tests are widely used in clinical neuropsychology. We propose the standardization and clinical validation of a new SVF test based on the production of names of birds and articles of furniture (Birds and Articles of Furniture test-BAF).

METHODS

A sample of 268 subjects aged 40 years or more underwent the test. The clinical validation was conducted on subjects affected by amnesic Mild Cognitive Impairment (aMCI; N = 106), mild (N = 178), and moderate (N = 114) Alzheimer's disease (AD).

RESULTS

The BAF total score was influenced by both age and education, whereas the single scores obtained on BAF were also influenced by gender. The percentage of subjects with pathological score on BAF increased from aMCI (19%) to mild (45.5%) and moderate (71.1%) AD, and receiver operating characteristic curves analysis showed that the BAF may be highly reliable in distinguishing aMCI and AD patients from healthy subjects. We also provide typicality norms for birds and articles of furniture that could be useful in the assessment of qualitative features of words produced in semantic fluency tests.

CONCLUSIONS

The BAF test could be a valid and reliable tool in both clinical practice and research on subjects affected by cognitive impairment.

Adverse vascular risk is related to cognitive decline in older adults

BACKGROUND

Cardiovascular disease (CVD) and related risk factors are associated with Alzheimer's disease (AD). This association is less well-defined in normal cognition (NC) or prodromal AD (mild cognitive impairment, MCI).

OBJECTIVE

Cross-sectionally and longitudinally relate a vascular risk index to cognitive outcomes among elders free of clinical dementia.

METHODS

3,117 MCI (74 ± 8 years, 56% female) and 6,603 NC participants (72 ± 8 years, 68% female) were drawn from the National Alzheimer's Coordinating Center. A composite measure of vascular risk was defined using the Framingham Stroke Risk Profile (FSRP) score (i.e., age, systolic blood pressure, anti-hypertensive medication, diabetes, cigarette smoking, CVD history, atrial fibrillation). Ordinary linear regressions and generalized linear mixed models related baseline FSRP to cross-sectional and longitudinal cognitive outcomes, separately for NC and MCI, adjusting for age, gender, race, education, and follow-up time (in longitudinal models).

RESULTS

In NC participants, increasing FSRP was related to worse baseline global cognition, information processing speed, and sequencing abilities (p-values <0.0001) and a worse longitudinal trajectory on all cognitive measures (p-values <0.0001). In MCI, increasing FSRP correlated with worse longitudinal delayed memory (p = 0.004). In secondary models using an age-excluded FSRP score, associations persisted in NC participants for global cognition, naming, information processing speed, and sequencing abilities.

CONCLUSIONS

An adverse vascular risk profile is associated with worse cognitive trajectory, especially global cognition, naming, and information processing speed, among NC elders. Future studies are needed to understand how effective management of CVD and related risk factors can modify cognitive decline to identify the ideal timeframe for primary prevention implementation.

Visuoconstructional Impairment in Subtypes of Mild Cognitive Impairment

Clock Drawing Test performance was examined alongside other neuropsychological tests in mild cognitive impairment (MCI). We tested the hypothesis that clock-drawing errors are related to executive impairment. The current research examined 86 patients with MCI for whom, in prior research, cluster analysis was used to sort patients into dysexecutive (dMCI, n = 22), amnestic (aMCI, n = 13), and multidomain (mMCI, n = 51) subtypes. First, principal components analysis (PCA) and linear regression examined relations between clock-drawing errors and neuropsychological test performance independent of MCI subtype. Second, between-group differences were assessed with analysis of variance (ANOVA) where MCI subgroups were compared to normal controls (NC). PCA yielded a 3-group solution. Contrary to expectations, clock-drawing errors loaded with lower performance on naming/lexical retrieval, rather than with executive tests. Regression analyses found increasing clock-drawing errors to command were associated with worse performance only on naming/lexical retrieval tests. ANOVAs revealed no differences in clock-drawing errors between dMCI versus mMCI or aMCI versus NCs. Both the dMCI and mMCI groups generated more clock-drawing errors than the aMCI and NC groups in the command condition. In MCI, language-related skills contribute to clock-drawing impairment.

Regional vulnerability of longitudinal cortical association connectivity: Associated with structural network topology alterations in preterm children with cerebral palsy

Preterm born children with spastic diplegia type of cerebral palsy and white matter injury or periventricular leukomalacia (PVL), are known to have motor, visual and cognitive impairments. Most diffusion tensor imaging (DTI) studies performed in this group have demonstrated widespread abnormalities using averaged deterministic tractography and voxel-based DTI measurements. Little is known about structural network correlates of white matter topography and reorganization in preterm cerebral palsy, despite the availability of new therapies and the need for brain imaging biomarkers. Here, we combined novel post-processing methodology of probabilistic tractography data in this preterm cohort to improve spatial and regional delineation of longitudinal cortical association tract abnormalities using an along-tract approach, and compared these data to structural DTI cortical network topology analysis. DTI images were acquired on 16 preterm children with cerebral palsy (mean age 5.6 ± 4) and 75 healthy controls (mean age 5.7 ± 3.4). Despite mean tract analysis, Tract-Based Spatial Statistics (TBSS) and voxel-based morphometry (VBM) demonstrating diffusely reduced fractional anisotropy (FA) reduction in all white matter tracts, the along-tract analysis improved the detection of regional tract vulnerability. The along-tract map-structural network topology correlates revealed two associations: (1) reduced regional posterior-anterior gradient in FA of the longitudinal visual cortical association tracts (inferior fronto-occipital fasciculus, inferior longitudinal fasciculus, optic radiation, posterior thalamic radiation) correlated with reduced posterior-anterior gradient of intra-regional (nodal efficiency) metrics with relative sparing of frontal and temporal regions; and (2) reduced regional FA within frontal-thalamic-striatal white matter pathways (anterior limb/anterior thalamic radiation, superior longitudinal fasciculus and cortical spinal tract) correlated with alteration in eigenvector centrality, clustering coefficient (inter-regional) and participation co-efficient (inter-modular) alterations of frontal-striatal and fronto-limbic nodes suggesting re-organization of these pathways. Both along tract and structural topology network measurements correlated strongly with motor and visual clinical outcome scores. This study shows the value of combining along-tract analysis and structural network topology in depicting not only selective parietal occipital regional vulnerability but also reorganization of frontal-striatal and frontal-limbic pathways in preterm children with cerebral palsy. These finding also support the concept that widespread, but selective posterior-anterior neural network connectivity alterations in preterm children with cerebral palsy likely contribute to the pathogenesis of neurosensory and cognitive impairment in this group.

Structural Image Analysis of the Brain in Neuropsychology Using Magnetic Resonance Imaging (MRI) Techniques

Magnetic resonance imaging (MRI) of the brain provides exceptional image quality for visualization and neuroanatomical classification of brain structure. A variety of image analysis techniques provide both qualitative as well as quantitative methods to relate brain structure with neuropsychological outcome and are reviewed herein. Of particular importance are more automated methods that permit analysis of a broad spectrum of anatomical measures including volume, thickness and shape. The challenge for neuropsychology is which metric to use, for which disorder and the timing of when image analysis methods are applied to assess brain structure and pathology. A basic overview is provided as to the anatomical and pathoanatomical relations of different MRI sequences in assessing normal and abnormal findings. Some interpretive guidelines are offered including factors related to similarity and symmetry of typical brain development along with size-normalcy features of brain anatomy related to function. The review concludes with a detailed example of various quantitative techniques applied to analyzing brain structure for neuropsychological outcome studies in traumatic brain injury.

Operationalizing mild cognitive impairment criteria in small vessel disease: the VMCI-Tuscany Study

INTRODUCTION

Mild cognitive impairment (MCI) prodromic of vascular dementia is expected to have a multidomain profile.

METHODS

In a sample of cerebral small vessel disease (SVD) patients, we assessed MCI subtypes distributions according to different operationalization of Winblad criteria and compared the neuroimaging features of single versus multidomain MCI. We applied three MCI diagnostic scenarios in which the cutoffs for objective impairment and the number of considered neuropsychological tests varied.

RESULTS

Passing from a liberal to more conservative diagnostic scenarios, of 153 patients, 5% were no longer classified as MCI, amnestic multidomain frequency decreased, and nonamnestic single domain increased. Considering neuroimaging features, severe medial temporal lobe atrophy was more frequent in multidomain compared with single domain.

DISCUSSION

Operationalizing MCI criteria changes the relative frequency of MCI subtypes. Nonamnestic single domain MCI may be a previously nonrecognized type of MCI associated with SVD.

Mild cognitive impairment etiologic subtyping using pragmatic and conventional criteria: preliminary experience in the Florence VAS-COG clinic

BACKGROUND

Mild cognitive impairment (MCI) is an abnormal condition defined by the presence of cognitive decline not severe enough to fit dementia criteria. According to Winblad et al.'s criteria, the clinical distinction of MCI subtypes (amnestic/non-amnestic, single/multiple domain) is based on the cognitive profiling (conventional diagnosis) and infers possible different MCI etiologies. MCI prodromic of vascular dementia (Vasc-MCI) is thought to be characterized by a multiple domain profile. In our outpatient clinic (the "Florence VAS-COG clinic"), the diagnosis of MCI and of its different subtypes (vascular, degenerative, mixed) is based on a comprehensive evaluation of clinical and neuroimaging features (pragmatic diagnosis).

AIMS

To compare the pragmatic and conventional diagnoses in terms of etiologic subtyping of MCI.

METHODS

We retrospectively assessed the agreement between the two diagnoses in 30 MCI patients. Agreement was considered present when degenerative MCI was of the amnestic type (single or multiple domain) and Vasc-MCI was of the multiple domain type (amnestic or non-amnestic MCI).

RESULTS

In 15/30 (50 %) patients, the diagnoses were in disagreement: 5/9 (56 %) patients diagnosed with a degenerative MCI type presented a non-amnestic cognitive profile (4 single domain and 1 multiple domain); 10/21 (48 %) Vasc-MCI were classified as non-amnestic single domain.

CONCLUSIONS

The application of MCI etiologic subtyping using pragmatic or conventional diagnoses leads to different results. In our setting, not all the Vasc-MCI patients have a multiple domain profile. Our preliminary study suggests that the cognitive profile of Vasc-MCI is more heterogeneous than previously suggested.

White matter signal abnormality quality differentiates mild cognitive impairment that converts to Alzheimer's disease from nonconverters

The objective of this study was to assess how longitudinal change in the quantity and quality of white matter signal abnormalities (WMSAs) contributes to the progression from mild cognitive impairment (MCI) to Alzheimer's disease (AD). The Mahalanobis distance of WMSA from normal-appearing white matter using T1-, T2-, and proton density-weighted MRI was defined as a quality measure for WMSA. Cross-sectional analysis of WMSA volume in 104 cognitively healthy older adults, 116 individuals with MCI who converted to AD within 3 years (mild cognitive impairment converter [MCI-C]), 115 individuals with MCI that did not convert in that time (mild cognitive impairment nonconverter [MCI-NC]), and 124 individuals with AD from the Alzheimer's Disease Neuroimaging Initiative revealed that WMSA volume was substantially greater in AD relative to the other groups but did not differ between MCI-NC and MCI-C. Longitudinally, MCI-C exhibited faster WMSA quality progression but not volume compared with matched MCI-NC beginning 18 months before MCI-C conversion to AD. The strongest difference in rate of change was seen in the time period starting 6 months before MCI-C conversion to AD and ending 6 months after conversion (p < 0.001). The relatively strong effect in this time period relative to AD conversion in the MCI-C was similar to the relative rate of change in hippocampal volume, a traditional imaging marker of AD pathology. These data demonstrate changes in white matter tissue properties that occur within WMSA in individuals with MCI that will subsequently obtain a clinical diagnosis of AD within 18 months. Individuals with AD have substantially greater WMSA volume than all MCI suggesting that there is a progressive accumulation of WMSA with progressive disease severity, and that quality change predates changes in this total volume. Given the timing of the changes in WMSA tissue quality relative to the clinical diagnosis of AD, these findings suggest that WMSAs are a critical component for this conversion and are a critical component of this clinical syndrome.

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

BACKGROUND

We assessed whether mild cognitive impairment (MCI) subtypes could be empirically derived within the Alzheimer's Disease Neuroimaging Initiative (ADNI) MCI cohort and examined associated biomarkers and clinical outcomes.

METHODS

Cluster analysis was performed on neuropsychological data from 825 MCI ADNI participants.

RESULTS

Four subtypes emerged: (1) dysnomic (n = 153), (2) dysexecutive (n = 102), (3) amnestic (n = 288), and (4) cluster-derived normal (n = 282) who performed within normal limits on cognitive testing. The cluster-derived normal group had significantly fewer APOE ε4 carriers and fewer who progressed to dementia compared with the other subtypes; they also evidenced cerebrospinal fluid Alzheimer's disease biomarker profiles that did not differ from the normative reference group.

CONCLUSIONS

Identification of empirically derived MCI subtypes demonstrates heterogeneity in MCI cognitive profiles that is not captured by conventional criteria. The large cluster-derived normal group suggests that conventional diagnostic criteria are susceptible to false-positive errors, with the result that prior MCI studies may be diluting important biomarker relationships.

Subjective cognitive complaints contribute to misdiagnosis of mild cognitive impairment

Subjective cognitive complaints are a criterion for the diagnosis of mild cognitive impairment (MCI), despite their uncertain relationship to objective memory performance in MCI. We aimed to examine self-reported cognitive complaints in subgroups of the Alzheimer's Disease Neuroimaging Initiative (ADNI) MCI cohort to determine whether they are a valuable inclusion in the diagnosis of MCI or, alternatively, if they contribute to misdiagnosis. Subgroups of MCI were derived using cluster analysis of baseline neuropsychological test data from 448 ADNI MCI participants. Cognitive complaints were assessed via the Everyday Cognition (ECog) questionnaire, and discrepancy scores were calculated between self- and informant-report. Cluster analysis revealed Amnestic and Mixed cognitive phenotypes as well as a third Cluster-Derived Normal subgroup (41.3%), whose neuropsychological and cerebrospinal fluid (CSF) Alzheimer's disease (AD) biomarker profiles did not differ from a "robust" normal control group. This cognitively intact phenotype of MCI participants overestimated their cognitive problems relative to their informant, whereas Amnestic MCI participants with objective memory impairment underestimated their cognitive problems. Underestimation of cognitive problems was associated with positive CSF AD biomarkers and progression to dementia. Overall, there was no relationship between self-reported cognitive complaints and objective cognitive functioning, but significant correlations were observed with depressive symptoms. The inclusion of self-reported complaints in MCI diagnostic criteria may cloud rather than clarify diagnosis and result in high rates of misclassification of MCI. Discrepancies between self- and informant-report demonstrate that overestimation of cognitive problems is characteristic of normal aging while underestimation may reflect greater risk for cognitive decline.

Using neuroimaging to inform clinical practice for the diagnosis and treatment of mild cognitive impairment

Advances in structural and functional neuroimaging techniques have unquestionably improved understanding of the development and progression of Alzheimer disease (AD), with evidence supporting regional (and network) change that underlies cognitive decline across the "healthy" aging/mild cognitive impairment (MCI)/AD spectrum. This review focuses on visual rating scales and volumetric analyses that could be easily integrated into clinical practice, followed by a review of functional neuroimaging findings suggesting that widespread cerebral dysfunction underlies the learning and memory deficits in MCI. Evidence of preserved neuroplasticity in this population and that cognitive rehabilitation techniques may capitalize on this plasticity to improve cognition in those with MCI is also discussed.

Mild cognitive impairment: a concept and diagnostic entity in need of input from neuropsychology

This virtual issue consists of studies previously published in the Journal of the International Neuropsychological Society and selected on the basis of their content related to one of the most highly researched concepts in behavioral neurology and neuropsychology over the past decade: mild cognitive impairment (MCI). The reliance on cognitive screening measures, staging-based rating scales, and limited neuropsychological testing in diagnosing MCI across most research studies may miss individuals with subtle cognitive declines or mis-diagnose MCI in those who are otherwise cognitively normal on a broader neuropsychological battery of tests. The assembled articles highlight the perils of relying on these conventional criteria for MCI diagnosis and reveal how the reliability of diagnosis is improved when sound neuropsychological approaches are adopted. When these requirements are met, we illustrate with a second series of articles that neuropsychological measures associate strongly with biomarkers and often reflect pathology beyond or instead of typical AD distributions. The final set of articles reveal that people with MCI demonstrate mild but identifiable functional difficulties, and a challenge for neuropsychology is how to incorporate this information to better define MCI and distinguish it from early dementia. Neuropsychology is uniquely positioned to improve upon the state of the science in MCI research and practice by providing critically important empirical information on the specific cognitive domains affected by the predominant neurodegenerative disorders of late life as well as on the diagnostic decision-making strategies used in studies. When such efforts to more comprehensively assess neuropsychological functions are undertaken, better characterizations of spared and impaired cognitive and functional abilities result and lead to more convincing associations with other biomarkers as well as to prediction of clinical outcomes.

Neuropsychological criteria for mild cognitive impairment improves diagnostic precision, biomarker associations, and progression rates

We compared two methods of diagnosing mild cognitive impairment (MCI): conventional Petersen/Winblad criteria as operationalized by the Alzheimer's Disease Neuroimaging Initiative (ADNI) and an actuarial neuropsychological method put forward by Jak and Bondi designed to balance sensitivity and reliability. 1,150 ADNI participants were diagnosed at baseline as cognitively normal (CN) or MCI via ADNI criteria (MCI: n = 846; CN: n = 304) or Jak/Bondi criteria (MCI: n = 401; CN: n = 749), and the two MCI samples were submitted to cluster and discriminant function analyses. Resulting cluster groups were then compared and further examined for APOE allelic frequencies, cerebrospinal fluid (CSF) Alzheimer's disease (AD) biomarker levels, and clinical outcomes. Results revealed that both criteria produced a mildly impaired Amnestic subtype and a more severely impaired Dysexecutive/Mixed subtype. The neuropsychological Jak/Bondi criteria uniquely yielded a third Impaired Language subtype, whereas conventional Petersen/Winblad ADNI criteria produced a third subtype comprising nearly one-third of the sample that performed within normal limits across the cognitive measures, suggesting this method's susceptibility to false positive diagnoses. MCI participants diagnosed via neuropsychological criteria yielded dissociable cognitive phenotypes, significant CSF AD biomarker associations, more stable diagnoses, and identified greater percentages of participants who progressed to dementia than conventional MCI diagnostic criteria. Importantly, the actuarial neuropsychological method did not produce a subtype that performed within normal limits on the cognitive testing, unlike the conventional diagnostic method. Findings support the need for refinement of MCI diagnoses to incorporate more comprehensive neuropsychological methods, with resulting gains in empirical characterization of specific cognitive phenotypes, biomarker associations, stability of diagnoses, and prediction of progression. Refinement of MCI diagnostic methods may also yield gains in biomarker and clinical trial study findings because of improvements in sample compositions of 'true positive' cases and removal of 'false positive' cases.

Neuropsychological criteria for mild cognitive impairment improves diagnostic precision, biomarker associations, and progression rates

We compared two methods of diagnosing mild cognitive impairment (MCI): conventional Petersen/Winblad criteria as operationalized by the Alzheimer's Disease Neuroimaging Initiative (ADNI) and an actuarial neuropsychological method put forward by Jak and Bondi designed to balance sensitivity and reliability. 1,150 ADNI participants were diagnosed at baseline as cognitively normal (CN) or MCI via ADNI criteria (MCI: n = 846; CN: n = 304) or Jak/Bondi criteria (MCI: n = 401; CN: n = 749), and the two MCI samples were submitted to cluster and discriminant function analyses. Resulting cluster groups were then compared and further examined for APOE allelic frequencies, cerebrospinal fluid (CSF) Alzheimer's disease (AD) biomarker levels, and clinical outcomes. Results revealed that both criteria produced a mildly impaired Amnestic subtype and a more severely impaired Dysexecutive/Mixed subtype. The neuropsychological Jak/Bondi criteria uniquely yielded a third Impaired Language subtype, whereas conventional Petersen/Winblad ADNI criteria produced a third subtype comprising nearly one-third of the sample that performed within normal limits across the cognitive measures, suggesting this method's susceptibility to false positive diagnoses. MCI participants diagnosed via neuropsychological criteria yielded dissociable cognitive phenotypes, significant CSF AD biomarker associations, more stable diagnoses, and identified greater percentages of participants who progressed to dementia than conventional MCI diagnostic criteria. Importantly, the actuarial neuropsychological method did not produce a subtype that performed within normal limits on the cognitive testing, unlike the conventional diagnostic method. Findings support the need for refinement of MCI diagnoses to incorporate more comprehensive neuropsychological methods, with resulting gains in empirical characterization of specific cognitive phenotypes, biomarker associations, stability of diagnoses, and prediction of progression. Refinement of MCI diagnostic methods may also yield gains in biomarker and clinical trial study findings because of improvements in sample compositions of 'true positive' cases and removal of 'false positive' cases.

Blood pressure and cognition among older adults: a meta-analysis

Hypertension has adverse effects on cognition, can alter cerebral vasculature integrity, and is associated with the pathogenesis of dementia. Using meta-analysis, we correlated blood pressure to multiple cognitive domains among older adults free of clinical stroke and dementia. We identified 230 studies indexed in PubMed and PsycINFO relating blood pressure and cognition. After applying exclusion criteria, we selected n = 12 articles with n = 4,076 participants (age range 43-91 years). Meta-analysis yielded an association between blood pressure and episodic memory (r = -.18, p < .001) and between blood pressure and global cognition (r = -.07, p < .001). When limiting analyses to studies adjusting for vascular covariates (n = 8, n = 2,141), blood pressure was modestly related to global cognition (r = -.11, p < .001), attention (r = .14, p = .002), and episodic memory (r = -.20, p < .001) with a trend for language (r = -.22, p = .07). Findings underscore the need to manage blood pressure as a key prevention method in minimizing abnormal cognitive aging prior to the onset of clinical dementia.

Are empirically-derived subtypes of mild cognitive impairment consistent with conventional subtypes?

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

Modeling the heterogeneity in risk of progression to Alzheimer's disease across cognitive profiles in mild cognitive impairment

Introduction

Heterogeneity in risk of conversion to Alzheimer's disease (AD) among individuals with mild cognitive impairment (MCI) is well known. Novel statistical methods that are based on partially ordered set (poset) models can be used to create models that provide detailed and accurate information about performance with specific cognitive functions. This approach allows for the study of direct links between specific cognitive functions and risk of conversion to AD from MCI. It also allows for further delineation of multi-domain amnestic MCI, in relation to specific non-amnestic cognitive deficits, and the modeling of a range of episodic memory functioning levels.

Methods

From the Alzheimer's Disease Neuroimaging Initiative (ADNI) study, conversion at 24 months of 268 MCI subjects was analyzed. It was found that 101 of those subjects (37.7%) converted to AD within that time frame. Poset models were then used to classify cognitive performance for MCI subjects. Respective observed conversion rates to AD were calculated for various cognitive subgroups, and by APOE e4 allele status. These rates were then compared across subgroups.

Results

The observed conversion rate for MCI subjects with a relatively lower functioning with a high level of episodic memory at baseline was 61.2%. In MCI subjects who additionally also had relatively lower perceptual motor speed functioning and at least one APOE e4 allele, the conversion rate was 84.2%. In contrast, the observed conversion rate was 9.8% for MCI subjects with a relatively higher episodic memory functioning level and no APOE e4 allele. Relatively lower functioning with cognitive flexibility and perceptual motor speed by itself also appears to be associated with higher conversion rates.

Conclusions

Among MCI subjects, specific baseline cognitive profiles that were derived through poset modeling methods, are clearly associated with differential rates of conversion to AD. More precise delineation of MCI by such cognitive functioning profiles, including notions such as multidomain amnestic MCI, can help in gaining further insight into how heterogeneity arises in outcomes. Poset-based modeling methods may be useful for providing more precise classification of cognitive subgroups among MCI for imaging and genetics studies, and for developing more efficient and focused cognitive test batteries.

Mismatch negativity/P3a complex in young people with psychiatric disorders: a cluster analysis

BACKGROUND

We have recently shown that the event-related potential biomarkers, mismatch negativity (MMN) and P3a, are similarly impaired in young patients with schizophrenia- and affective-spectrum psychoses as well as those with bipolar disorder. A data driven approach may help to further elucidate novel patterns of MMN/P3a amplitudes that characterise distinct subgroups in patients with emerging psychiatric disorders.

METHODS

Eighty seven outpatients (16 to 30 years) were assessed: 19 diagnosed with a depressive disorder; 26 with a bipolar disorder; and 42 with a psychotic disorder. The MMN/P3a complex was elicited using a two-tone passive auditory oddball paradigm with duration deviant tones. Hierarchical cluster analysis utilising frontal, central and temporal neurophysiological variables was conducted.

RESULTS

Three clusters were determined: the 'globally impaired' cluster (n = 53) displayed reduced frontal and temporal MMN as well as reduced central P3a amplitudes; the 'largest frontal MMN' cluster (n = 17) were distinguished by increased frontal MMN amplitudes and the 'largest temporal MMN' cluster (n = 17) was characterised by increases in temporal MMN only. Notably, 55% of those in the globally impaired cluster were diagnosed with schizophrenia-spectrum disorder, whereas the three patient subgroups were equally represented in the remaining two clusters. The three cluster-groups did not differ in their current symptomatology; however, the globally impaired cluster was the most neuropsychologically impaired, compared with controls.

CONCLUSIONS

These findings suggest that in emerging psychiatric disorders there are distinct MMN/P3a profiles of patient subgroups independent of current symptomatology. Schizophrenia-spectrum patients tended to show the most global impairments in this neurophysiological complex. Two other subgroups of patients were found to have neurophysiological profiles suggestive of quite different neurobiological (and hence, treatment) implications.

Relationship between cortical microinfarcts and cognitive impairment in Alzheimer's disease

Cerebrovascular disease and AD pathology co-exist in most dementia cases, and microinfarcts (MIs), particularly if cortical and multiple, play an additive and independent role in AD cognitive impairment. The main cause of cortical MIs is chronic cerebral hypoperfusion but occlusive vascular diseases, embolism and blood-brain barrier disruptions, isolated or combined, may also play a role. The precise mechanisms by which MIs cause cognitive impairment are not well known, but one plausible explanation is that they are widespread and accompanied by diffuse hypoperfusion, hypoxia, oxidative stress and inflammation, particularly in the watershed areas of the tertiary association cortex, and hence could damage cognition networks and explain many of AD's cognitive and behavioral disturbances. Therefore, it is crucial to control vascular risk factors and avoid uncontrolled use of the antihypertensives, neuroleptics and other sedative drugs frequently prescribed to AD patients.

Dysexecutive syndrome and cerebrovascular disease in non-amnestic mild cognitive impairment: A systematic review of the literature

Objective

Non-amnestic dysexecutive Vascular Mild Cognitive Impairment (VaMCI) may represent preclinical Vascular Dementia (VaD). The aim of this study was to summarize the clinical, neuropsychological and neuroimaging aspects of VaMCI; and to assess its patterns of progression to dementia.

Methods

Searches were made in the ISI Web of Knowledge, PubMed and Lilacs databases, using the terms "mild cognitive impairment" and "executive function". Altogether, 944 articles were retrieved.

Results

VaMCI cases had poorer performances on fronto-executive tasks, a higher prevalence of stroke, presence of periventricular and profound white matter hyperintensities on MRI images, as well as more extrapyramidal signs and behavioral symptoms. Executive dysfunction might be associated with disconnection of fronto-parietal-subcortical circuits. Progression to dementia was associated with baseline deficits in executive function, in simple sustained attention and language, and large periventricular WMH.

Discussion

VaMCI develops with impairment in non-memory domains and subcortical white matter changes on MRI images, which are consistent with clinical and neuroimaging findings in VaD.

Posterior cingulum white matter disruption and its associations with verbal memory and stroke risk in mild cognitive impairment

Medial temporal lobe and temporoparietal brain regions are among the earliest neocortical sites to undergo pathophysiologic alterations in Alzheimer's disease (AD), although the underlying white matter changes in these regions is less well known. We employed diffusion tensor imaging to evaluate early alterations in regional white matter integrity in participants diagnosed with mild cognitive impairment (MCI). The following regions of interests (ROIs) were examined: 1) anterior cingulum (AC); 2) posterior cingulum (PC); 3) genu of the corpus callosum; 4) splenium of the corpus callosum; and 5) as a control site for comparison, posterior limb of the internal capsule. Forty nondemented participants were divided into demographically-similar groups based on cognitive status (MCI: n = 20; normal control: n = 20), and fractional anisotropy (FA) estimates of each ROI were obtained. MCI participants showed greater posterior white matter (i.e., PC, splenium) but not anterior white matter (i.e., AC, genu) changes, after adjusting for age, stroke risk, and whole brain volume. FA differences of the posterior white matter were best accounted for by changes in radial but not axial diffusivity. PC FA was also significantly positively correlated with hippocampal volume as well as with performance on tests of verbal memory, whereas stroke risk was significantly correlated with genu FA and was unrelated to PC FA. When investigating subtypes of our MCI population, amnestic MCI participants showed lower PC white matter integrity relative to those with non-amnestic MCI. Findings implicate involvement of posterior microstructural white matter degeneration in the development of MCI-related cognitive changes and suggest that reduced FA of the PC may be a candidate neuroimaging marker of AD risk.

Depressive symptom severity is related to poorer cognitive performance in prodromal Huntington disease

OBJECTIVE

Depression is associated with more severe cognitive deficits in many neurological disorders, though the investigation of this relationship in Huntington disease (HD) has been limited. This study examined the relationship between depressive symptom severity and measures of executive functioning, learning/memory, and attention in prodromal HD.

METHOD

Participants (814 prodromal HD, 230 gene-negative) completed a neuropsychological test battery and the Beck Depression Inventory-II (BDI-II). Based on the BDI-II, there were 637 participants with minimal depression, 89 with mild depression, 61 with moderate depression, and 27 with severe depression in the prodromal HD group.

RESULTS

ANCOVA (controlling for age, sex, and education) revealed that performance on SDMT, Trails B, Hopkins Verbal Learning Test--Revised (HVLT-R) Immediate Recall, and Stroop interference was significantly different between the BDI-II severity groups, with the moderate and severe groups performing worse than the minimal and mild groups. There were no significant differences between the BDI-II severity groups for Trails A or HVLT-R Delayed Recall. Linear regression revealed that both gene status and depression severity were significant predictors of performance on all cognitive tests examined, with contributions of BDI-II and gene status comparable for Trails A, SDMT, and Stroop interference. Gene status had a higher contribution for HVLT-R Immediate and Delayed Recall and Trails B.

CONCLUSIONS

Our results suggest that depressive symptom severity is related to poorer cognitive performance in individuals with prodromal HD. Though there are currently no approved therapies for cognitive impairment in HD, our findings suggest that depression may be a treatable contributor to cognitive impairment in this population.

Distinct neurometabolic profiles are evident in the anterior cingulate of young people with major psychiatric disorders

Currently, there are no validated neurobiological methods for distinguishing different pathophysiological pathways in young patients presenting in the early phases of major psychiatric disorders. Hence, treatments are delivered simply on the basis of their possible effects on nonspecific symptom constructs such as depression, cognitive change or psychotic symptoms. In this study, the ratios (relative to creatine) of key metabolites (N-acetyl aspartate, myoinositol, glutamate and glutathione) were measured with proton magnetic resonance spectroscopy ((1)H-MRS) within the anterior cingulate cortex of 88 young persons presenting with major mood or psychotic symptoms. We derived empirically (using a cluster analytical technique) three subgroups of subjects on the basis of their patterns of in vivo brain biochemistry. The three subgroups were distinguished (from each other) by all the four metabolites, in particular, glutathione and glutamate. By contrast, the groups could not be distinguished by differences in terms of other demographic, functional or clinical measures. We propose that this (1)H-MRS-based subclassification system could be used as the basis for much more specific tests of novel intervention strategies (notably, antioxidant and glutamatergic therapies) early in the course of major psychiatric disorders.

White matter predictors of cognitive functioning in older adults

Few studies have applied multiple imaging modalities to examine cognitive correlates of white matter. We examined the utility of T2-weighted magnetic resonance imaging (MRI) -derived white matter hyperintensities (WMH) and diffusion tensor imaging-derived fractional anisotropy (FA) to predict cognitive functioning among older adults. Quantitative MRI and neuropsychological evaluations were performed in 112 older participants from an ongoing study of the genetics of Alzheimer's disease (AD) in African Americans. Regional WMH volumes and FA were measured in multiple regions of interest. We examined the association of regional WMH and an FA summary score with cognitive test performance. Differences in WMH and FA were compared across diagnostic groups (i.e., normal controls, mild cognitive impairment, and probable AD). Increased WMH volume in frontal lobes was associated with poorer delayed memory performance. FA did not emerge as a significant predictor of cognition. White matter hyperintensity volume in the frontal and parietal lobes was increased in MCI participants and more so in AD patients relative to controls. These results highlight the importance of regionally distributed small vessel cerebrovascular disease in memory performance and AD among African American older adults. White matter microstructural changes, quantified with diffusion tensor imaging, appear to play a lesser role in our sample.

The profile of executive functioning in amnestic mild cognitive impairment: disproportionate deficits in inhibitory control

Amnestic mild cognitive impairment (aMCI) represents a group of individuals who are highly likely to develop Alzheimer's disease (AD). Although aMCI is typically conceptualized as involving predominantly deficits in episodic memory, recent studies have demonstrated that deficits in executive functioning may also be present, and thorough categorization of cognitive functioning in MCI may improve early diagnosis and treatment of AD. We first provide an extensive review of neuropsychology studies that examined executive functioning in MCI. We then present data on executive functioning across multiple sub-domains (divided attention, working memory, inhibitory control, verbal fluency, and planning) in 40 aMCI patients (single or multiple domain) and 32 normal elderly controls (NECs). MCI patients performed significantly worse than NECs in all 5 sub-domains, and there was impairment (>1.0 SD below the mean of NECs) in all sub-domains. Impairment on each test was frequent, with 100% of MCI patients exhibiting a deficit in at least one sub-domain of executive functioning. Inhibitory control was the most frequently and severely impaired. These results indicate that executive dysfunction in multiple sub-domains is common in aMCI and highlights the importance of a comprehensive neuropsychological evaluation for fully characterizing the nature and extent of cognitive deficits in MCI.

Specific measures of executive function predict cognitive decline in older adults

Decline in executive function has been noted in the prodromal stage of Alzheimer's disease (AD) and may presage more global cognitive declines. In this prospective longitudinal study, five measures of executive function were used to predict subsequent global cognitive decline in initially nondemented older adults. Of 71 participants, 15 demonstrated significant decline over a 1-year period on the Dementia Rating Scale (Mattis, 1988) and the remaining participants remained stable. In the year before decline, the decline group performed significantly worse than the no-decline group on two measures of executive function: the Color-Word Interference Test (CWIT; inhibition/switching condition) and Verbal Fluency (VF; switching condition). In contrast, decliners and non-decliners performed similarly on measures of spatial fluency (Design Fluency switching condition), spatial planning (Tower Test), and number-letter switching (Trail Making Test switching condition). Furthermore, the CWIT inhibition-switching measure significantly improved the prediction of decline and no-decline group classification beyond that of learning and memory measures. These findings suggest that some executive function measures requiring inhibition and switching provide predictive utility of subsequent global cognitive decline independent of episodic memory and may further facilitate early detection of dementia.

Dysexecutive functioning in mild cognitive impairment: derailment in temporal gradients

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