Serum interleukin (IL)-15 as a biomarker of Alzheimer's disease

Interleukin (IL-15), a pro-inflammatory cytokine has been studied as a possible marker of Alzheimer’s disease (AD); however its exact role in neuro-inflammation or the pathogenesis AD is not well understood yet. A Multiple Indicators Multiple Causes (MIMIC) approach was used to examine the relationship between serum IL-15 levels and AD in a well characterized AD cohort, the Texas Alzheimer's Research and Care Consortium (TARCC). Instead of categorical diagnoses, we used two latent construct d (for dementia) and g’ (for cognitive impairments not contributing to functional impairments) in our analysis. The results showed that the serum IL-15 level has significant effects on cognition, exclusively mediated by latent construct d and g’. Contrasting directions of association lead us to speculate that IL-15’s effects in AD are mediated through functional networks as d scores have been previously found to be specifically related to default mode network (DMN). Our finding warrants the need for further research to determine the changes in structural and functional networks corresponding to serum based biomarkers levels.

Ethnicity moderates dementia's biomarkers

We have employed structural equation models to explicitly distinguish functional status, and therefore "dementia-relevant" variance in cognitive task performance (i.e., "δ"). We previously associated δ with cytokines and other serum biomarkers in a well characterized Alzheimer's disease cohort, the Texas Alzheimer's Research and Care Consortium. However, that δ homolog did not exhibit factor equivalence across ethnicity. In this study, we construct a δ homolog that exhibits mean and factor equivalence across ethnicity [i.e., "d(=)"]. d(=) is associated significantly with ten of the twelve previously selected biomarkers. Most of these associations are again specific to Non-Hispanic White participants. These findings have yet to be validated in other cohorts, but may suggest cross-ethnic differences in dementia's pathobiological mechanisms between Hispanic Mexican-Americans and Non-Hispanic Whites.

The temporospatial evolution of neuritic plaque-related and independent tauopathies: implications for dementia staging

Neuritic plaque (NP) formation can be dated in vivo. This analysis attempts to "date" the progression of neurofibrillary tangles (NFT) using the spatial distribution of NP as a reference. Autopsy data from 471 participants in the Honolulu-Asia Aging Study (HAAS) were combined into latent factor measures of NFT and NP counts. The variance in "early" and "late" NP pathology was used to estimate the spatial distribution of "early" and "late" NFT formation. A third latent factor representing "non-NP-related NFT" was also constructed. "Early" NP and "late" NP correlated significantly with objectively early and later cognitive performance, respectively. In contrast to our expectations, neocortical NFT correlated best with "early" NP pathology, while NFT in allocortical structures correlated best with "late" NP pathology. Therefore, the NP-related fraction of NFT appears to be co-localized spatially with NP. However, since the latter evolve corticofugally in time, this suggests that NP-related NFT do so as well. Corticotropic NFT formation must therefore be either unrelated to NP formation, a temporally distinct process, or both.

Telephone screening for mild cognitive impairment in hispanics using the Alzheimer's questionnaire

BACKGROUND/STUDY CONTEXT: There is a need for a simple and reliable screening test to detect individuals with mild cognitive impairment (MCI). The authors analyzed the relationship between performance of the Alzheimer's Questionnaire (AQ), an informant-rated measure of dementia-related behaviors, relative to the Telephone Interview for Cognitive Status-modified (TICS-m), Memory Impairment Scale-telephone version (MIS-t), and the Telephone Executive Assessment (TEXAS) as predictors of MCI.

METHODS

Comparative cross-sectional design, with data collected from participants in the Texas Alzheimer's Research and Care Consortium's (TARCC) San Antonio site. One-hundred percent of our sample was Hispanic. The San Antonio subset of TARCC sample is highly enriched with Mexican Americans (MAs). Fifty-five percent of the interviews were conducted in Spanish. Of the 184 persons enrolled, 124 were normal controls (NCs), and 60 participants had MCI. MCI status and Clinical Dementia Rating Scale Sum of Boxes (CDR-SOB) were determined through clinical consensus and performed blind to telephone assessments. Controlling for age, gender, education, and language of interview, the association between telephone measures and CDR-SOB was evaluated by multivariate regression.

RESULTS

AQ scores were not affected by education, gender, and language of interview, but subject's age did show a positive correlation with informant AQ ratings. The AQ predicted CDR-SOB independently of the cognitive measures, adding variance above and beyond demographics. The TICS-m and the TEXAS appear to have additive value in improving the detection of cognitively impaired patients. The MIS-t failed to contribute significantly to CDR-SOB, independent of the other measures.

CONCLUSION

The AQ may have utility as a culture-fair telephone screening for MCI. The AQ was able to modestly distinguish MCI from NCs. The TEXAS adds variance to a model of dementia severity independent of the AQ, suggesting that the latter may weakly assess that cognitive domain (executive control function). On the other hand, the AQ attenuates the MIS-t effect. This suggests a prominent AQ bias in favor of detecting memory impairment. Additional studies are required to determine if the AQ can distinguish between amnestic and dysexecutive MCI subtypes, or between MCI and Alzheimer's disease in Hispanics.

"Executive functions" cannot be distinguished from general intelligence: two variations on a single theme within a symphony of latent variance

The empirical foundation of executive control function (ECF) remains controversial. We have employed structural equation models (SEM) to explicitly distinguish domain-specific variance in executive function (EF) performance from memory (MEM) and shared cognitive performance variance, i.e., Spearman's “g.” EF does not survive adjustment for both MEM and g in a well fitting model of data obtained from non-demented older persons (N = 193). Instead, the variance in putative EF measures is attributable only to g, and related to functional status only through a fraction of that construct (i.e., “d”). d is a homolog of the latent variable δ, which we have previously associated specifically with the Default Mode Network (DMN). These findings undermine the validity of EF and its putative association with the frontal lobe. ECF may have no existence independent of general intelligence, and no functionally salient association with the frontal lobe outside of that structure's contribution to the DMN.

Validation of a latent construct for dementia case-finding in Mexican-Americans

We have constructed a latent dementia proxy, "δ", and validated it in several datasets, including well characterized subjects participating in the Texas Alzheimer's Research and Care Consortium (TARCC) study. It may be possible to construct δ homologs from almost any ad hoc combination of cognitive and functional status measures. δ homologs may also be relatively immune to measurement error, including cultural, linguistic, or educational biases. These properties make factor scores derived from latent variables a potentially attractive solution for dementia case-finding in rural or minority populations. Here we have explored an alternative and briefer assessment by which to construct a δ homolog and validate the resulting latent variable (dMA) in Mexican-American (MA) TARCC subjects. dMA, composed of simple "bedside" dementia screening instruments, achieves Areas Under the Receiver Operative Curve that rival those of δ itself. Ethnicity has a small effect on dMA's performance. These results suggest that it may be possible to validly export dMA into other MA populations, or to export δ homolog factor scores from one population to another.

Latent variables may be useful in pain's assessment

Background

Unobserved “latent” variables have the potential to minimize “measurement error” inherent to any single clinical assessment or categorical diagnosis.

Objectives

To demonstrate the potential utility of latent variable constructs in pain’s assessment.

Design

We created two latent variables representing depressive symptom-related pain (Pd) and its residual, “somatic” pain (Ps), from survey questions.

Setting

The Hispanic Established Population for Epidemiological Studies in the Elderly (H-EPESE) project, a longitudinal population-based cohort study.

Participants

Community dwelling elderly Mexican-Americans in five Southwestern U.S. states. The data were collected in the 7th HEPESE wave in 2010 (N = 1,078).

Measurements

Self-reported pain, Center for Epidemiological Studies Depression Scale (CES-D) scores, bedside cognitive performance measures, and informant-rated measures of basic and instrumental Activities of Daily Living.

Results

The model showed excellent fit [χ² = 20.37, DF = 12; p = 0.06; Comparative fit index (CFI) = 0.998; Root mean statistical error assessment (RMSEA) = 0.025]. Ps was most strongly indicated by self-reported pain-related physician visits (r = 0.48, p ≤0.001). Pd was most strongly indicated by self-reported pain-related sleep disturbances (r = 0.65, p <0.001). Both Pd and Ps were significantly independently associated with chronic pain (> one month), regional pain and pain summed across selected regions. Pd alone was significantly independently associated with self-rated health, life satisfaction, self-reported falls, Life-space, nursing home placement, the use of opiates, and a variety of sleep related disturbances. Ps was associated with the use of NSAIDS. Neither construct was associated with declaration of a resuscitation preference, mode of resuscitation preference declaration, or with opting for a “Do Not Resuscitate” (DNR) order.

Conclusion

This analysis illustrates the potential of latent variables to parse observed data into “unbiased” constructs with unique predictive profiles. The latent constructs, by definition, are devoid of measurement error that affects any subset of their indicators. Future studies could use such phenotypes as outcome measures in clinical pain management trials or associate them with potential biomarkers using powerful parametric statistical methods.

The default mode network may be the key substrate of depressive symptom-related cognitive changes

Depressive symptoms are associated with an increased risk of Alzheimer's disease (AD) but the mechanism(s) involved has not been well established. In a convenience sample of participants in the University of Kansas' Brain Aging Project, we use structural equation modeling (SEM) to explicitly distinguish depressive symptom-related variance in cognitive task performance (i.e., DEPCOG) from that which is unrelated to a depressive symptoms. DEPCOG is strongly associated with the cognitive correlates of functional status (δ), which we previously associated with elements of the Default Mode Network (DMN). Both δ and DEPCOG map to a posterior cingulate seeded network that has recently been associated with amyloid-β deposition and includes elements of the DMN. Both contribute significantly to clinical dementia status and dementia severity, as measured by the Clinical Dementia Rating Scale Sum of Boxes. These findings suggest that the cognitive correlates of depressive symptoms, even in the absence of a major depressive episode, may contribute to dementia in their own right, and could be responsible for some cases of incident clinical "AD". This conclusion suggests new opportunities for the latter's diagnosis, prevention, and treatment.

Does ethnicity moderate dementia's biomarkers?

We have used structural equation models to explicitly distinguish functional status, and therefore "dementia-relevant" variance in cognitive task performance (i.e., "δ") from that which is unrelated to a dementing process. Our approach results in a relatively "error-free" continuous variable that can serve as a dementia-specific phenotype. In this study, we associate δ with cytokines and other serum biomarkers in a well characterized Alzheimer's disease cohort, the Texas Alzheimer's Research and Care Consortium. Independent of covariates, δ is associated significantly with 12 serum biomarkers. These associations appear to be specific to non-Hispanic white participants.

Alzheimer's disease pathology does not mediate the association between depressive symptoms and subsequent cognitive decline

BACKGROUND

Depressive symptoms in nondemented individuals appear to hasten the progression from mild cognitive impairment to clinical Alzheimer's disease (AD) and double the risk of incident AD. However, the mechanism(s) by which depression might affect this risk has not been well established. The purpose of this analysis was to test the hypothesis that AD pathology mediates depression's apparent effect on the risk of dementia conversion using longitudinally collected psychometric testing and autopsy data from the Honolulu-Asia Aging Study.

METHODS

Latent factor variables representing AD, cortical Lewy body (CLB), and ischemic neuropathology were tested as potential mediators of the association between the Center for Epidemiological Studies depression scale (CES-D) score and the 10-year prospective rate of cognitive decline, adjusted for baseline cognition, age, education, total number of medications, and brain weight at autopsy.

RESULTS

CES-D scores, neurofibrillary tangle counts, CLB counts, and ischemic lesions each made significant independent contributions to cognitive decline. However, CES-D scores were not significantly associated with any pathological variable; thus the pathological variables were not mediators of the effect of CES-D scores on cognitive decline.

CONCLUSIONS

Subsyndromal depressive symptoms are significantly associated with subsequent cognitive decline. Although the effect is relatively modest, it is stronger than that of amyloid-related neuropathologies and independent of that of neurofibrillary tangles, cortical Lewy bodies, and ischemic lesions. Our results argue against the role of AD-related neuropathology as a mediator of depression's effect on cognitive decline, but cannot rule out a significant mediation effect in a subset of cases, perhaps with more severe baseline depressive symptoms.

The default mode network and related right hemisphere structures may be the key substrates of dementia

We have employed structural equation models to explicitly distinguish dementia-relevant variance in cognitive task performance (i.e., δ) from the variance that is unrelated to a dementing process (i.e., g'). Together g' and d comprise Spearman's "g". Although d represents only a minor fraction of the total variance in cognitive task performance, it is more strongly associated with dementia severity than is g'. In this analysis, we replicate δ in a new dataspace, the University of Kansas Brain Aging Project, and associate it specifically with regional grey matter atrophy by voxel-based morphometry of magnetic resonance imaging data. The latent variable d localizes to elements of the default mode network and related structures in the R hemisphere.

Estimating the temporal evolution of Alzheimer's disease pathology with autopsy data

The temporal growth of Alzheimer's disease (AD) neuropathology cannot be easily determined because autopsy data are available only after death. We combined autopsy data from 471 participants in the Honolulu-Asia Aging Study (HAAS) into latent factor measures of neurofibrillary tangle and neuritic plaque counts. These were associated with intercept and slope parameters from a latent growth curve (LGC) model of 9-year change in cognitive test performance in 3244 autopsied and non-autopsied HAAS participants. Change in cognition fully mediated the association between baseline cognitive performance and AD lesions counts. The mediation effect of cognitive change on both AD lesion models effectively dates them within the period of cognitive surveillance. Additional analyses could lead to an improved understanding of lesion propagation in AD.

Fortress brain

Neurodegenerative diseases are associated with neuronal inclusions, comprised of protein aggregates. In Alzheimer's Disease (AD) and Lewy Body Disease (LBD) such lesions are distributed in a hierarchical retrograde transynaptic spatial pattern. This implies a retrograde transynaptic temporal propagation as well. There can be few explanations for this other than infectious agents (prions and viruses). This suggests that AD and LBD (at least) may have infectious origins. Transynaptic infiltration of the CNS along cranial nerve or other major projections, by one or more infectious agents has important implications. The clinical syndrome and natural history of each neurodegenerative disorder will reflect its portal of entry. There may be a different neurodegenerative syndrome for each cranial nerve or other portal of entry, and not all may manifest as "dementia". Each syndrome may be associated with more than one pathological lesion. Each pathology may be associated with several clinical syndromes. Host-parasite interactions are species specific. This may explain the rarity of AD-like pathology in most other older mammals. Over evolutionary timescales, the human brain should be adapted to predation by neurotropic agents. Viewed from this perspective, the prion-like pro-inflammatory and pro-apoptotic properties of β-amyloid and other proteins may be adaptive, and anti-microbial. Reductions in synaptic density may slow the progress of invading pathogens, while perineuronal nets and other structures may guard the gates. This suggests a defense in depth of a structure, the brain, that is inherently vulnerable to invasion along its neural networks.

Validation of a latent variable representing the dementing process

The cognitive correlates of functional status are essential to dementia case-finding. Nevertheless, cognitive performance is a generally weak predictor of functional outcomes. We have employed structural equation models to explicitly distinguish functional status, and therefore "dementia-relevant" variance in cognitive task performance (i.e., δ) from the variance that is unrelated to a dementing process (i.e., g'). Together, g' + δ encompass Spearman's g. Although δ represents only a small fraction of the total variance in cognitive task performance, it is more strongly associated with dementia status than is g'. In this study, we validate δ in a well characterized Alzheimer's disease cohort, the Texas Alzheimer's Research and Care Consortium. Our approach results in "error free" continuous variables. This suggests that δ can serve as a dementia specific endophenotype. As a result, future studies may be able to associate δ with inflammatory and genetic biomarkers.

Getting Past "g": testing a new model of dementing processes in persons without dementia

The cognitive correlates of functional status are essential to dementia case-finding. The authors have used structural-equation models to explicitly distinguish dementia-relevant variance in cognitive task performance (i.e., δ) from the variance that is unrelated to a dementing process (i.e., g'). Together, g' and δ comprise Spearman's "g." Although δ represents only a small fraction of the total variance in cognitive task performance, it is more strongly associated with dementia severity than is g'. In this analysis, the authors test whether δ can predict future cognitive decline in persons clinically without dementia at baseline. These results have implications for the clinical assessment of dementia and suggest that functional status should assume a more important role.

Depressive symptoms predict longitudinal change in executive control but not memory

OBJECTIVE

Depression in non-demented persons has been identified as a possible risk factor for incident Alzheimer's disease (AD).

METHODS

Latent Growth Curve models were developed of baseline depressive symptoms as a predictor of longitudinal changes in cognition. Depressive symptoms were assessed using the 15-item Geriatric Depression Scale (GDS). Memory was assessed by the California Verbal Learning Task (CVLT). Executive control function (ECF) was assessed by the Executive Interview (EXIT25) and Trail-Making Test Part B (Trails-B). Five hundred forty-seven non-institutionalized older retirees living in a single comprehensive care retirement community participated.

RESULTS

Depressive symptoms were significantly associated only with the 3-year rate of decline in psychomotor speed, as measured by Trails A, and ECF, as measured by the EXIT25. Both associations withstood adjustment for age, gender, education, and baseline level of care.

CONCLUSIONS

Depressive symptoms are associated with longitudinal decline in cognition. However, this association selectively involves executive control, not memory, and possibly only a subset of 'executive' functions. Although depressive symptoms may hasten conversion from mild cognitive impairment (MCI) to dementia, depression-related conversion is not likely to be mediated by evolution of the AD pathological process.

Modeling regional vulnerability to Alzheimer pathology

Latent growth curve (LGC) models estimate change over time in a cohort's serially obtained measurements. We have applied LGC techniques to a spatial distribution of Alzheimer's disease (AD) pathology using autopsy data from 435 participants in the Honolulu-Asia Aging Study. Neurofibrillary tangle (NFT) and neuritic plaques (NP) were distributed across differently ordered sets of anatomical regions. The gradient of spatial change in neuritic plaque (dNP), was significantly associated with that of neurofibrillary tangle (dNFT), but weakly and inversely (r = -0.12; p < 0.001). Both dNFT and dNP correlated significantly and inversely with Braak stage. Sixty-one percent of the variance in Braak stage was explained by dNFT independent of covariates. Only dNFT was significantly associated with longitudinal change in cognition. Only dNP was associated with apolipoprotein (APOE) e4 burden. This is the first application of LGC models to spatially-ordered data. The result is a quantification of the interindividual variation in the interregional vulnerability to Alzheimer's disease lesions.

Meta-analysis of 123I-MIBG cardiac scintigraphy for the diagnosis of Lewy body-related disorders

Patients with parkinsonism pose a diagnostic challenge. Parkinson's disease may be difficult to distinguish from multiple system atrophy and progressive supranuclear palsy, whereas Parkinson's disease and dementia with Lewy bodies can be difficult to distinguish from Alzheimer's disease and other dementias. A number of studies have found diminished cardiac (123) I-metaiodobenzylguanidine uptake in Lewy body-related conditions (Parkinson's disease and Lewy body dementia). In 2005, the Dementia With Lewy Bodies Consortium considered (123) I-metaiodobenzylguanidine cardiac scintigraphy a "supportive" diagnostic feature, based on limited evidence. We report a meta-analysis of the literature and an assessment of the utility of (123) I-metaiodobenzylguanidine for the diagnosis of dementia with Lewy bodies and Parkinson's disease. A search was conducted of articles published between 1950 and June 2010. Forty-six studies involving neuropsychiatric and movement disorders, comprising 2680 subjects, were included in the analysis. A mixed-effects regression model was used to analyze the delayed mean heart-to-mediastinum ratio of (123) I-metaiodobenzylguanidine uptake. (123) I-metaiodobenzylguanidine cardiac scintigraphy sensitively detected and specifically distinguished 2 diagnostic clusters: (1) Parkinson's disease, dementia with Lewy bodies, and rapid eye movement sleep behavior disorder; and (2) normal controls and patients with Alzheimer's disease, multiple system atrophy, progressive supranuclear palsy, vascular dementia, and frontotemporal dementia. The area under the receiver operating characteristic curve was 0.987 at a cluster discriminatory heart-to-mediastinum ratio threshold of 1.77. This threshold yielded 94% sensitivity and 91% specificity for the discrimination of these diagnostic clusters. (123) I-metaiodobenzylguanidine cardiac scintigraphy can accurately distinguish between 2 movement disorders, Parkinson's disease and multiple system atrophy, and between 2 common causes of dementia, Alzheimer's disease and dementia with Lewy bodies. © 2011 Movement Disorder Society.