Risk-reducing Apolipoprotein E and Clusterin genotypes protect against the consequences of poor vascular health on executive function performance and change in nondemented older adults

Utility of the Comprehensive Trail Making Test in the Assessment of Mild Cognitive Impairment in Older Patients

INTRODUCTION

The purpose of this study is to determine the usefulness of the CTMT (Comprehensive Trail Making Test) in diagnosing mild cognitive impairment in older patients. The test is used to assess executive functions, of which impairment is already observed in the early stages of the neurodegenerative process.

MATERIALS AND METHODS

The study includes 98 patients of a geriatric ward assigned to 2 groups of 49 patients each: patients diagnosed with a mild cognitive impairment and patients without a cognitive impairment, constituting the control group (group K). A set of screening tests was used in the initial study: the MMSE (Mini-Mental State Examination), MoCA (Montreal Cognitive Assessment), and CDT (Clock Drawing Test), GDS (Geriatric Depression Scale). The second study included the performance of the CTMT; the performance indicator was the time of performance.

RESULTS

Statistically significant differences are obtained between patients with mild cognitive impairments and those in cognitive normality in the performance of the CTMT test (p < 0.01). Patients with MCIs took longer to complete all trails of the test. To identify cognitive impairment, cutoff points were proposed for the CTMT total score and the other test trails. The CTMT overall score and CTMT 5 scored the highest AUCs (CTMT overall score = 0.77, CTMT Trail 5 = 0.80).

CONCLUSIONS

The Comprehensive Trail Making Test may be useful in diagnosing mild cognitive impairment as a complementary screening tool.

Bridging Integrator 1 (BIN1, rs6733839) and Sex Are Moderators of Vascular Health Predictions of Memory Aging Trajectories

Background: A promising risk loci for sporadic Alzheimer’s disease (AD), Bridging Integrator 1 (BIN1), is thought to operate through the tau pathology pathway. Objective: We examine BIN1 risk for a moderating role with vascular health (pulse pressure; PP) and sex in predictions of episodic memory trajectories in asymptomatic aging adults. Methods: The sample included 623 participants (Baseline Mean age = 70.1; 66.8% female) covering a 44-year longitudinal band (53–97 years). With an established memory latent variable arrayed as individualized trajectories, we applied Mplus 8.5 to determine the best fitting longitudinal growth model. Main analyses were conducted in three sequential phases to investigate: 1) memory trajectory prediction by PP, 2) moderation by BIN1 genetic risk, and 3) stratification by sex. Results: We first confirmed that good vascular health (lower PP) was associated with higher memory level and shallower decline and males were more severely affected by worsening PP in both memory performance and longitudinal decline. Second, the PP prediction of memory trajectories was significant for BIN1 C/C and C/T carriers but not for persons with the highest AD risk (T/T homozygotes). Third, when further stratified by sex, the BIN1 moderation of memory prediction by PP was selective for females. Conclusion: We observed a novel interaction whereby BIN1 (linked with tauopathy in AD) and sex sequentially moderated a benchmark PP prediction of differential memory decline in asymptomatic aging. This multi-modal biomarker interaction approach, disaggregated by sex, can be an effective method for enhancing precision of AD genetic risk assessment.

Brain atrophy trajectories predict differential functional performance in Alzheimer's disease: Moderations with apolipoprotein E and sex

INTRODUCTION

We examine whether distinct brain atrophy patterns (using brain parenchymal fraction [BPF]) differentially predict functional performance and decline in Alzheimer's disease (AD), and are independently moderated by (1) a key AD genetic risk marker (apolipoprotein E [APOE]), (2) sex, and (3) high-risk group (women APOE ɛ4 carriers).

METHODS

We used a 2-year longitudinal sample of AD patients (baseline N = 170; mean age = 71.3 [9.1] years) from the Sunnybrook Dementia Study. We applied latent class analysis, latent growth modeling, and path analysis. We aimed to replicate our findings (N = 184) in the Alzheimer's Disease Neuroimaging Initiative.

RESULTS

We observed that high brain atrophy class predicted lower functional performance and steeper decline. This association was moderated by APOE, sex, and high-risk group. Baseline findings as moderated by APOE and high-risk group were replicated.

DISCUSSION

Women APOE ɛ4 carriers may selectively be at a greater risk of functional impairment with higher brain atrophy.

A Multimodal Risk Network Predicts Executive Function Trajectories in Non-demented Aging

Background: Multiple modalities of Alzheimer's disease (AD) risk factors may operate through interacting networks to predict differential cognitive trajectories in asymptomatic aging. We test such a network in a series of three analytic steps. First, we test independent associations between three risk scores (functional-health, lifestyle-reserve, and a combined multimodal risk score) and cognitive [executive function (EF)] trajectories. Second, we test whether all three associations are moderated by the most penetrant AD genetic risk [Apolipoprotein E (APOE) ε4+ allele]. Third, we test whether a non-APOE AD genetic risk score further moderates these APOE × multimodal risk score associations. Methods: We assembled a longitudinal data set (spanning a 40-year band of aging, 53-95 years) with non-demented older adults (baseline n = 602; Mage = 70.63(8.70) years; 66% female) from the Victoria Longitudinal Study (VLS). The measures included for each modifiable risk score were: (1) functional-health [pulse pressure (PP), grip strength, and body mass index], (2) lifestyle-reserve (physical, social, cognitive-integrative, cognitive-novel activities, and education), and (3) the combination of functional-health and lifestyle-reserve risk scores. Two AD genetic risk markers included (1) APOE and (2) a combined AD-genetic risk score (AD-GRS) comprised of three single nucleotide polymorphisms (SNPs; Clusterin[rs11136000], Complement receptor 1[rs6656401], Phosphatidylinositol binding clathrin assembly protein[rs3851179]). The analytics included confirmatory factor analysis (CFA), longitudinal invariance testing, and latent growth curve modeling. Structural path analyses were deployed to test and compare prediction models for EF performance and change. Results: First, separate analyses showed that higher functional-health risk scores, lifestyle-reserve risk scores, and the combined score, predicted poorer EF performance and steeper decline. Second, APOE and AD-GRS moderated the association between functional-health risk score and the combined risk score, on EF performance and change. Specifically, only older adults in the APOEε4- group showed steeper EF decline with high risk scores on both functional-health and combined risk score. Both associations were further magnified for adults with high AD-GRS. Conclusion: The present multimodal AD risk network approach incorporated both modifiable and genetic risk scores to predict EF trajectories. The results add an additional degree of precision to risk profile calculations for asymptomatic aging populations.

Integrating Three Characteristics of Executive Function in Non-Demented Aging: Trajectories, Classification, and Biomarker Predictors

OBJECTIVE

With longitudinal executive function (EF) data from the Victoria Longitudinal Study, we investigated three research goals pertaining to key characteristics of EF in non-demented aging: (a) examining variability in EF longitudinal trajectories, (b) establishing trajectory classes, and (c) identifying biomarker predictors discriminating these classes.

METHOD

We used a trajectory analyses sample (n = 781; M age = 71.42) for the first and second goals and a prediction analyses sample (n = 570; M age = 70.10) for the third goal. Eight neuropsychological EF measures were used as indicators of three EF dimensions: inhibition, updating, and shifting. Data-driven classification analyses were applied to the full trajectory distribution. Machine learning prediction analyses tested 15 predictors from genetic, functional, lifestyle, mobility, and demographic risk domains.

RESULTS

First, we observed: (a) significant variability in EF trajectories over a 40-year band of aging and (b) significantly variable patterns of EF decline. Second, a four-class EF trajectory model was observed, characterized with classes differentiated by an algorithm of level and slope information. Third, the highest group class was discriminated from lowest by several prediction factors: more education, more novel cognitive activity, lower pulse pressure, younger age, faster gait, lower body mass index, and better balance.

CONCLUSION

First, with longitudinal variability in EF aging, the data-driven approach showed that long-term trajectories can be differentiated into separable classes. Second, prediction analyses discriminated class membership by a combination of multiple biomarkers from demographic, lifestyle, functional, and mobility domains of risk for brain and cognitive aging decline.

Association of Alzheimer's Disease Genetic Risk Loci with Cognitive Performance and Decline: A Systematic Review

The association of Apolipoprotein E (APOE) with late-onset Alzheimer's disease (LOAD) and cognitive endophenotypes of aging has been widely investigated. There is increasing interest in evaluating the association of other LOAD risk loci with cognitive performance and decline. The results of these studies have been inconsistent and inconclusive. We conducted a systematic review of studies investigating the association of non-APOE LOAD risk loci with cognitive performance in older adults. Studies published from January 2009 to April 2018 were identified through a PubMed database search using keywords and by scanning reference lists. Studies were included if they were either cross-sectional or longitudinal in design, included at least one genome-wide significant LOAD risk loci or a genetic risk score, and had one objective measure of cognition. Quality assessment of the studies was conducted using the quality of genetic studies (Q-Genie) tool. Of 2,466 studies reviewed, 49 met inclusion criteria. Fifteen percent of the associations between non-APOE LOAD risk loci and cognition were significant. However, these associations were not replicated across studies, and the majority were rendered non-significant when adjusting for multiple testing. One-third of the studies included genetic risk scores, and these were typically significant only when APOE was included. The findings of this systematic review do not support a consistent association between individual non-APOE LOAD risk and cognitive performance or decline. However, evidence suggests that aggregate LOAD genetic risk exerts deleterious effects on decline in episodic memory and global cognition.

Impacts of AD-Related ABCA7 and CLU Variants on Default Mode Network Connectivity in Healthy Middle-Age Adults

Objective

To investigate the impact of Alzheimer’s disease (AD)-related risk gene (ATP-binding cassette A7-ABCA7 and Clusterin-CLU) on the functional connectivity pattern of default mode network (DMN) in healthy middle-age adults.

Methods

A total of 147 healthy middle-aged volunteers were enrolled in this study. All subjects completed MRI scans, neuropsychological assessments, and AD-related genotyped analysis. All subjects were divided into high, middle and low risk groups according to the score of risk genotypes, which included CLU (rs11136000, rs2279590, rs9331888, and rs9331949) and ABCA7 (rs3764650 and rs4147929). The genetic effects of CLU, ABCA7, and CLU × ABCA7 on DMN functional connectivity pattern were further explored. Moreover, the genetic effect of Apolipoprotein ε4 (APOEε4) was also considered. Finally, correlation analysis was performed between the signals of brain regions with genetic effect and neuropsychological test scores.

Results

Compared with the low-risk group, the high-risk group of CLU showed decreased functional connectivity in posterior cingulate cortex (PCC) and the left middle frontal cortex (P < 0.05, GRF correction). As for the interaction between the CLU and ABCA7, all the subjects were divided into high, middle, and low risk group; the middle-risk group was divided into CLU and ABCA7-dominated middle-risk group. The function connectivity pattern of DMN among the three or four groups were distributed in the bilateral medial prefrontal cortex (MPFC) and bilateral superior frontal gyrus (SFG) (P < 0.05, GRF correction). When APOEε4 carriers were excluded, the CLU-predominant middle-risk group displayed the decreased functional connectivity in MPFC when compared with the low-risk group, while ABCA7-prodominant middle-risk group displayed decreased functional connectivity in cuneus when compared with the high-risk group (all P < 0.05, GRF correction). The z values of left middle frontal cortex were positively correlated with the scores of Serial Dotting Test (SDT) in high-risk group of CLU, while z values of MPFC and cuneus were positively correlated to the scores of Montreal Cognitive Assessment (MoCA) in low-risk group of three or four groups.

Conclusion

The functional connectivity of MPFC-PCC might be modulated by the interaction of CLU and ABCA7. Moreover, APOEε4 might be interacted with ABCA7 and CLU modulation in the middle-aged carriers.

Body mass index predicts cognitive aging trajectories selectively for females: Evidence from the Victoria Longitudinal Study

OBJECTIVE

Elevated body weight in midlife is an established risk factor for accelerated cognitive decline, impairment, and dementia. Research examining the impact of later-life body mass index (BMI) on normal cognitive aging has produced mixed results. There is a need for longitudinal designs, replication across multiple cognitive domains, and consideration of BMI effects in the context of important moderators. The present research examined (a) BMI prediction of neuropsychological performance and decline in executive function (EF), neurocognitive speed, and memory and (b) sex stratification of BMI effects.

METHOD

Participants (n = 869; 573 females; M age = 71.75, range = 53-85 years) were older adults from the Victoria Longitudinal Study. Latent growth modeling was used to examine BMI as a predictor of level and change in three latent variables of cognition. The data were then stratified by sex to test whether BMI effects differed for females and males. We adjusted for selected medical, psychosocial, and demographic characteristics.

RESULTS

Higher BMI predicted less decline in EF, neurocognitive speed, and memory. Interestingly, when the data were stratified by sex, higher BMI predicted less neuropsychological decline across domains for females only. BMI was unrelated to cognitive aging trajectories for males.

CONCLUSIONS

We found that elevated BMI was a risk-reducing factor for cognitive decline only for females. Results may be used to enhance the precision with which intervention protocols may target specific subgroups of older adults. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Metabolomics Analyses of Saliva Detect Novel Biomarkers of Alzheimer's Disease

Using a non-invasive biofluid (saliva), we apply a powerful metabolomics workflow for unbiased biomarker discovery in Alzheimer's disease (AD). We profile and differentiate Cognitively Normal (CN), Mild Cognitive Impairment (MCI), and AD groups. The workflow involves differential chemical isotope labeling liquid chromatography mass spectrometry using dansylation derivatization for in-depth profiling of the amine/phenol submetabolome. The total sample (N = 109) was divided in to the Discovery Phase (DP) (n = 82; 35 CN, 25 MCI, 22 AD) and a provisional Validation Phase (VP) (n = 27; 10 CN, 10 MCI, 7 AD). In DP we detected 6,230 metabolites. Pairwise analyses confirmed biomarkers for AD versus CN (63), AD versus MCI (47), and MCI versus CN (2). We then determined the top discriminating biomarkers and diagnostic panels. A 3-metabolite panel distinguished AD from CN and MCI (DP and VP: Area Under the Curve [AUC] = 1.000). The MCI and CN groups were best discriminated with a 2-metabolite panel (DP: AUC = 0.779; VP: AUC = 0.889). In addition, using positively confirmed metabolites, we were able to distinguish AD from CN and MCI with good diagnostic performance (AUC > 0.8). Saliva is a promising biofluid for both unbiased and targeted AD biomarker discovery and mechanism detection. Given its wide availability and convenient accessibility, saliva is a biofluid that can promote diversification of global AD biomarker research.

Frailty effects on non-demented cognitive trajectories are moderated by sex and Alzheimer's genetic risk

BACKGROUND

Age-related frailty reflects cumulative multisystem physiological and health decline. Frailty increases the risk of adverse brain and cognitive outcomes, including differential decline and dementia. In a longitudinal sample of non-demented older adults, we examine whether (a) the level and/or change in frailty predicts trajectories across three cognitive domains (memory, speed, and executive function (EF)) and (b) prediction patterns are modified by sex or Alzheimer's genetic risk (Apolipoprotein E (APOE)).

METHODS

Participants (n = 632; M age = 70.7, range 53-95; 3 waves) were from the Victoria Longitudinal Study. After computing a frailty index, we used latent growth modeling and path analysis to test the frailty effects on level and change in three latent variables of cognition. We tested two potential moderators by stratifying by sex and APOE risk (ε4+, ε4-).

RESULTS

First, frailty levels predicted speed and EF performance (level) and differential memory change slopes. Second, change in frailty predicted the rate of decline for both speed and EF. Third, sex moderation analyses showed that females were selectively sensitive to (a) frailty effects on memory change and (b) frailty change effects on speed change. In contrast, the frailty effects on EF change were stronger in males. Fourth, genetic moderation analyses showed that APOE risk (e4+) carriers were selectively sensitive to frailty effects on memory change.

CONCLUSION

In non-demented older adults, increasing frailty is strongly associated with the differential decline in cognitive trajectories. For example, higher (worse) frailty was associated with more rapid memory decline than was lower (better) frailty. These effects, however, are moderated by both genetic risk and sex.

A Network of Genetic Effects on Non-Demented Cognitive Aging: Alzheimer's Genetic Risk (CLU + CR1 + PICALM) Intensifies Cognitive Aging Genetic Risk (COMT + BDNF) Selectively for APOEɛ4 Carriers

BACKGROUND

Trajectories of complex neurocognitive phenotypes in preclinical aging may be produced differentially through selective and interactive combinations of genetic risk.

OBJECTIVE

We organize three possible combinations into a "network" of genetic risk indices derived from polymorphisms associated with normal and impaired cognitive aging, as well as Alzheimer's disease (AD). Specifically, we assemble and examine three genetic clusters relevant to non-demented cognitive trajectories: 1) Apolipoprotein E (APOE), 2) a Cognitive Aging Genetic Risk Score (CA-GRS; Catechol-O-methyltransferase + Brain-derived neurotrophic factor), and 3) an AD-Genetic Risk Score (AD-GRS; Clusterin + Complement receptor 1 + Phosphatidylinositol-binding clathrin assembly protein).

METHOD

We use an accelerated longitudinal design (n = 634; age range = 55-95 years) to test whether AD-GRS (low versus high) moderates the effect of increasing CA-GRS risk on executive function (EF) performance and change as stratified by APOE status (ɛ4+ versus ɛ4-).

RESULTS

APOEɛ4 carriers with high AD-GRS had poorer EF performance at the centering age (75 years) and steeper 9-year decline with increasing CA-GRS but this association was not present in APOEɛ4 carriers with low AD-GRS.

CONCLUSIONS

APOEɛ4 carriers with high AD-GRS are at elevated risk of cognitive decline when they also possess higher CA-GRS risk. Genetic risk from both common cognitive aging and AD-related indices may interact in intensification networks to differentially predict (1) level and trajectories of EF decline and (2) potential selective vulnerability for transitions into impairment and dementia.

Alzheimer's Biomarkers From Multiple Modalities Selectively Discriminate Clinical Status: Relative Importance of Salivary Metabolomics Panels, Genetic, Lifestyle, Cognitive, Functional Health and Demographic Risk Markers

Background: Among the neurodegenerative diseases of aging, sporadic Alzheimer’s disease (AD) is the most prevalent and perhaps the most feared. With virtually no success at finding pharmaceutical therapeutics for altering progressive AD after diagnosis, research attention is increasingly directed at discovering biological and other markers that detect AD risk in the long asymptomatic phase. Both early detection and precision preclinical intervention require systematic investigation of multiple modalities and combinations of AD-related biomarkers and risk factors. We extend recent unbiased metabolomics research that produced a set of metabolite biomarker panels tailored to the discrimination of cognitively normal (CN), cognitively impaired and AD patients. Specifically, we compare the prediction importance of these panels with five other sets of modifiable and non-modifiable AD risk factors (genetic, lifestyle, cognitive, functional health and bio-demographic) in three clinical groups.

Method: The three groups were: CN (n = 35), mild cognitive impairment (MCI; n = 25), and AD (n = 22). In a series of three pairwise comparisons, we used machine learning technology random forest analysis (RFA) to test relative predictive importance of up to 19 risk biomarkers from the six AD risk domains.

Results: The three RFA multimodal prediction analyses produced significant discriminating risk factors. First, discriminating AD from CN was the AD metabolite panel and two cognitive markers. Second, discriminating AD from MCI was the AD/MCI metabolite panel and two cognitive markers. Third, discriminating MCI from CN was the MCI metabolite panel and seven markers from four other risk modalities: genetic, lifestyle, cognition and functional health.

Conclusions: Salivary metabolomics biomarker panels, supplemented by other risk markers, were robust predictors of: (1) clinical differences in impairment and dementia and even; (2) subtle differences between CN and MCI. For the latter, the metabolite panel was supplemented by biomarkers that were both modifiable (e.g., functional) and non-modifiable (e.g., genetic). Comparing, integrating and identifying important multi-modal predictors may lead to novel combinations of complex risk profiles potentially indicative of neuropathological changes in asymptomatic or preclinical AD.

Clinical dementia severity associated with ventricular size is differentially moderated by cognitive reserve in men and women

Background

Interindividual differences in cognitive reserve (CR) are associated with complex and dynamic clinical phenotypes observed in cognitive impairment and dementia. We tested whether (1) CR early in life (E-CR; measured by education and IQ), (2) CR later in life (L-CR; measured by occupation), and (3) CR panel (CR-P) with the additive effects of E-CR and L-CR, act as moderating factors between baseline ventricular size and clinical dementia severity at baseline and across 2 years. We further examined whether this moderation is differentially represented by sex.

Methods

We examined a longitudinal model using patients (N = 723; mean age = 70.8 ± 9.4 years; age range = 38–90 years; females = 374) from the Sunnybrook Dementia Study. The patients represented Alzheimer’s disease (n = 439), mild cognitive impairment (n = 77), vascular cognitive impairment (n = 52), Lewy body disease (n = 30), and frontotemporal dementia (n = 125). Statistical analyses included (1) latent growth modeling to determine how clinical dementia severity changes over 2 years (measured by performance on the Dementia Rating Scale), (2) confirmatory factor analysis to establish a baseline E-CR factor, and (3) path analysis to predict dementia severity. Baseline age (continuous) and Apolipoprotein E status (ɛ4−/ɛ4+) were included as covariates.

Results

The association between higher baseline ventricular size and dementia severity was moderated by (1) E-CR and L-CR and (2) CR-P. This association was differentially represented in men and women. Specifically, men in only the low CR-P had higher baseline clinical dementia severity with larger baseline ventricular size. However, women in the low CR-P showed the (1) highest baseline dementia severity and (2) fastest 2-year decline with larger baseline ventricular size.

Conclusions

Clinical dementia severity associated with ventricular size may be (1) selectively moderated by complex and additive CR networks and (2) differentially represented by sex.

Trials registration

ClinicalTrials.gov, NCT01800214. Registered on 27 February 2013.

Electronic supplementary material

The online version of this article (10.1186/s13195-018-0419-2) contains supplementary material, which is available to authorized users.

Defining the Relationship Between Hypertension, Cognitive Decline, and Dementia: a Review

Hypertension is a highly prevalent condition which has been established as a risk factor for cardiovascular and cerebrovascular disease. Although the understanding of the relationship between cardiocirculatory dysfunction and brain health has improved significantly over the last several decades, it is still unclear whether hypertension constitutes a potentially treatable risk factor for cognitive decline and dementia. While it is clear that hypertension can affect brain structure and function, recent findings suggest that the associations between blood pressure and brain health are complex and, in many cases, dependent on factors such as age, hypertension chronicity, and antihypertensive medication use. Whereas large epidemiological studies have demonstrated a consistent association between high midlife BP and late-life cognitive decline and incident dementia, associations between late-life blood pressure and cognition have been less consistent. Recent evidence suggests that hypertension may promote alterations in brain structure and function through a process of cerebral vessel remodeling, which can lead to disruptions in cerebral autoregulation, reductions in cerebral perfusion, and limit the brain's ability to clear potentially harmful proteins such as β-amyloid. The purpose of the current review is to synthesize recent findings from epidemiological, neuroimaging, physiological, genetic, and translational research to provide an overview of what is currently known about the association between blood pressure and cognitive function across the lifespan. In doing so, the current review also discusses the results of recent randomized controlled trials of antihypertensive therapy to reduce cognitive decline, highlights several methodological limitations, and provides recommendations for future clinical trial design.

Executive function performance and change in aging is predicted by apolipoprotein E, intensified by catechol-O-methyltransferase and brain-derived neurotrophic factor, and moderated by age and lifestyle

Recent studies have reported several genetic, health, and aging interaction effects in predicting cognitive performance and change. We used an accelerated longitudinal design to examine interactions among genetic, lifestyle, and aging for executive function (EF) in non-demented older adults (n = 634; age range = 53-95 years). The polymorphisms were apolipoprotein E (APOE), catechol-O-methyltransferase (COMT), and brain-derived neurotrophic factor (BDNF). We tested (1) independent and additive effects of APOE, COMT, and BDNF and (2) APOE effect modification for COMT + BDNF, on EF performance and 9-year change as separated by age and lifestyle activities. First, APOE ε4+ carriers had poorer EF performance and steeper 9-year decline. Second, APOE ε4+ carriers with (1) BDNF Met/Met genotype and (2) increasing allelic risk in the COMT + BDNF risk panel had poorer EF performance; these effects were moderated by lifestyle activities (composite of everyday social, physical, and cognitive activities). Examining APOE effect modification for COMT + BDNF risk panel effects with other moderating factors may help identify complex neurobiological and genetic underpinnings of polygenic phenotypes such as EF in aging.