Circulating biomarkers that predict incident dementia

Associations Between Plasma, Imaging, and Cerebrospinal Fluid Biomarkers with Driving Behavior and Cognitive Tests: Implications for Biomarker Usefulness

Background

Declines in instrumental activities of daily living like driving are hallmarks sequelae of Alzheimer's disease (AD). Although driving has been shown to be associated with traditional imaging and cerebrospinal fluid (CSF) biomarkers, it is possible that some biomarkers have stronger associations with specific aspects of driving behavior. Furthermore, associations between newer plasma biomarkers and driving behaviors are unknown.

Objective

This study assessed the extent to which individual plasma, imaging, and CSF biomarkers are related to specific driving behaviors and cognitive functions among cognitively normal older adults.

Methods

We analyzed naturalistic driving behavior from cognitively healthy older drivers (N = 167, 47% female, mean age = 73.3 years). All participants had driving, clinical, and demographic data and completed biomarker testing, including imaging, CSF, and/or plasma, within two years of study commencement.

Results

AD biomarkers were associated with different characteristics of driving and cognitive functioning within the same individuals. Elevated levels of plasma Aβ40 were associated with more speeding incidents, higher levels of CSF tau were related to shorter duration of trips, and higher CSF neurofilament light chain values were associated with traveling shorter distances, smaller radius of gyration, and fewer trips at night. We demonstrated that plasma, like CSF and imaging biomarkers, were helpful in predicting everyday driving behaviors.

Conclusions

These findings suggest that different biomarkers offer complementary information with respect to driving behaviors. These distinct relationships may help in understanding how different biological changes that occur during the preclinical stage of AD can impact various sensorimotor and cognitive processes.

Anti-Alzheimer activity of new coumarin-based derivatives targeting acetylcholinesterase inhibition

New 2-oxo-chromene-7-oxymethylene acetohydrazide derivatives 4a-d were designed and synthesized with a variety of bioactive chemical fragments. The newly synthesized compounds were evaluated as acetylcholinesterase (AChE) inhibitors and antioxidant agents in comparison to donepezil and ascorbic acid, respectively. Compound 4c exhibited a promising inhibitory impact with an IC₅₀ value of 0.802 μM and DPPH scavenging activity of 57.14 ± 2.77%. Furthermore, biochemical and haematological studies revealed that compound 4c had no effect on the blood profile, hepatic enzyme levels (AST, ALT, and ALP), or total urea in 4c-treated rats compared to the controls. Moreover, the histopathological studies of 4c-treated rats revealed the normal architecture of the hepatic lobules and renal parenchyma, as well as no histopathological damage in the examined hepatic, kidney, heart, and brain tissues. In addition, an in vivo study investigated the amelioration in the cognitive function of AD-rats treated with 4c through the T-maze and beam balance behavioural tests. Also, 4c detectably ameliorated MDA and GSH, reaching 90.64 and 27.17%, respectively, in comparison to the standard drug (90.64% and 35.03% for MDA and GSH, respectively). The molecular docking study exhibited a good fitting of compound 4c in the active site of the AChE enzyme and a promising safety profile. Compound 4c exhibited a promising anti-Alzheimer's disease efficiency compared to the standard drug donepezil.

Proteome Network Analysis Identifies Potential Biomarkers for Brain Aging

BACKGROUND

Alzheimer's disease and related dementias (ADRD) involve biological processes that begin years to decades before onset of clinical symptoms. The plasma proteome can offer insight into brain aging and risk of incident dementia among cognitively healthy adults.

OBJECTIVE

To identify biomarkers and biological pathways associated with neuroimaging measures and incident dementia in two large community-based cohorts by applying a correlation-based network analysis to the plasma proteome.

METHODS

Weighted co-expression network analysis of 1,305 plasma proteins identified four modules of co-expressed proteins, which were related to MRI brain volumes and risk of incident dementia over a median 20-year follow-up in Framingham Heart Study (FHS) Offspring cohort participants (n = 1,861). Analyses were replicated in the Cardiovascular Health Study (CHS) (n = 2,117, mean 6-year follow-up).

RESULTS

Two proteomic modules, one related to protein clearance and synaptic maintenance (M2) and a second to inflammation (M4), were associated with total brain volume in FHS (M2: p = 0.014; M4: p = 4.2×10-5). These modules were not significantly associated with hippocampal volume, white matter hyperintensities, or incident all-cause or AD dementia. Associations with TCBV did not replicate in CHS, an older cohort with a greater burden of comorbidities.

CONCLUSIONS

Proteome networks implicate an early role for biological pathways involving inflammation and synaptic function in preclinical brain atrophy, with implications for clinical dementia.

Artificial Intelligence and Circulating Cell-Free DNA Methylation Profiling: Mechanism and Detection of Alzheimer's Disease

Background: Despite extensive efforts, significant gaps remain in our understanding of Alzheimer’s disease (AD) pathophysiology. Novel approaches using circulating cell-free DNA (cfDNA) have the potential to revolutionize our understanding of neurodegenerative disorders. Methods: We performed DNA methylation profiling of cfDNA from AD patients and compared them to cognitively normal controls. Six Artificial Intelligence (AI) platforms were utilized for the diagnosis of AD while enrichment analysis was used to elucidate the pathogenesis of AD. Results: A total of 3684 CpGs were significantly (adj. p-value < 0.05) differentially methylated in AD versus controls. All six AI algorithms achieved high predictive accuracy (AUC = 0.949−0.998) in an independent test group. As an example, Deep Learning (DL) achieved an AUC (95% CI) = 0.99 (0.95−1.0), with 94.5% sensitivity and specificity. Conclusion: We describe numerous epigenetically altered genes which were previously reported to be differentially expressed in the brain of AD sufferers. Genes identified by AI to be the best predictors of AD were either known to be expressed in the brain or have been previously linked to AD. We highlight enrichment in the Calcium signaling pathway, Glutamatergic synapse, Hedgehog signaling pathway, Axon guidance and Olfactory transduction in AD sufferers. To the best of our knowledge, this is the first reported genome-wide DNA methylation study using cfDNA to detect AD.

Diagnostic accuracy of blood biomarkers for Alzheimer's disease and amnestic mild cognitive impairment: A meta-analysis

OBJECTIVE

To examine the diagnostic accuracy of blood-based biomarkers for detecting Alzheimer's disease (AD) and amnestic mild cognitive impairment (aMCI).

METHODS

Seven electronic databases were comprehensively searched for studies evaluating the diagnostic accuracy of blood-based biomarkers for detecting AD or aMCI up to July 31, 2020. The pooled sensitivity, specificity, and the diagnostic odds ratio (DOR) were calculated using a hierarchical summary receiver operating characteristic model.

RESULTS

A total of 17 studies (n = 2,083) were included. In differentiating patients with AD from the controls, the DOR was 32.2 for the plasma Aβ42 (sensitivity = 88 %, specificity = 81 %), 29.1 for the plasma Aβ oligomer (sensitivity = 80 %, specificity = 88 %), and 52.1 for the plasma tau (sensitivity = 90 %, specificity = 87 %). For differentiating aMCI from the controls, the DOR was 60.4 for the plasma Aβ42 (sensitivity = 86 %, specificity = 90 %) and 49.1 for the plasma tau (sensitivity = 79 %, specificity = 94 %). The use of ultra-high sensitive technology explained the heterogeneity in the diagnostic performance of blood-based biomarkers (P =  .01).

CONCLUSIONS

We suggest that blood-based biomarkers are minimally invasive and cost-effective tools for detecting AD; however, the evidence for detecting aMCI was still limited.

Relationship of Established Cardiovascular Risk Factors and Peripheral Biomarkers on Cognitive Function in Adults at Risk of Cognitive Deterioration

BACKGROUND

There is a paucity of information on the role of microvascular and inflammatory biomarkers in cognitive dysfunction.

OBJECTIVE

This study sought to evaluate the relationships between established and a number of peripheral biomarkers on cognitive patterns in 108 older adults with memory complaints.

METHODS

Participants in the AIBL Active study aged 60 years and older with at least one vascular risk factor and memory complaints completed a neuropsychological test battery and provided cross-sectional health data. Linear regression models adjusted for covariates examined associations between cognitive performance and a panel of vascular risk factors (Framingham cardiovascular scores, hs-CRP, homocysteine, fasting glucose, LDL-cholesterol) and peripheral biomarkers (TNF-α, BDNF, VCAM-1, ICAM-1, PAI-1, CD40L).

RESULTS

Higher fasting glucose and homocysteine levels were independent factors associated with poorer performance in Trail Making Test (TMT) B (adjusted β= 0.40±0.10 and 0.43±0.09, respectively). Increasing homocysteine levels were weakly associated with poorer global cognition and delayed recall (adjusted β= 0.23±0.10 and -0.20±0.10 respectively). Increasing Framingham cardiovascular scores were related to poorer performance in TMT B (β  = 0.42±0.19). There was early evidence of associations between increasing plasma TNF-α and poorer TMT B (adjusted β  = 0.21±0.10) and between increasing BDNF and better global cognition (β= -0.20±0.09).

CONCLUSION

This study provides evidence to support the associations between vascular risk factors (Framingham scores, fasting glucose, and homocysteine) and poorer cognitive functions. Additionally, we measured several peripheral biomarkers to further investigate their associations with cognition. The relationship between TNF-α, BDNF, and cognitive performance in various domains may offer new insights into potential mechanisms in vascular cognitive impairment.

The value of the GP's clinical judgement in predicting dementia: a multicentre prospective cohort study among patients in general practice

BACKGROUND

Clinical judgement is intrinsic to diagnostic strategies in general practice; however, empirical evidence for its validity is sparse.

AIM

To ascertain whether a GP's global clinical judgement of future cognitive status has an added value for predicting a patient's likelihood of experiencing dementia.

DESIGN AND SETTING

Multicentre prospective cohort study among patients in German general practice that took place from January 2003 to October 2016.

METHOD

Patients without baseline dementia were assessed with neuropsychological interviews over 12 years; 138 GPs rated the future cognitive decline of their participating patients. Associations of baseline predictors with follow-up incident dementia were analysed with mixed-effects logistic and Cox regression.

RESULTS

A total of 3201 patients were analysed over the study period (mean age = 79.6 years, 65.3% females, 6.7% incident dementia in 3 years, 22.1% incident dementia in 12 years). Descriptive analyses and comparison with other cohorts identified the participants as having frequent and long-lasting doctor-patient relationships and being well known to their GPs. The GP baseline rating of future cognitive decline had significant value for 3-year dementia prediction, independent of cognitive test scores and patient's memory complaints (GP ratings of very mild (odds ratio [OR] 1.97, 95% confidence intervals [95% CI] = 1.28 to 3.04); mild (OR 3.00, 95% CI = 1.90 to 4.76); and moderate/severe decline (OR 5.66, 95% CI = 3.29 to 9.73)). GPs' baseline judgements were significantly associated with patients' 12-year dementia-free survival rates (Mantel-Cox log rank test P<0.001).

CONCLUSION

In this sample of patients in familiar doctor-patient relationships, the GP's clinical judgement holds additional value for predicting dementia, complementing test performance and patients' self-reports. Existing and emerging primary care-based dementia risk models should consider the GP's judgement as one predictor. Results underline the importance of the GP-patient relationship.

Two novel blood-based biomarker candidates measuring degradation of tau are associated with dementia: A prospective study

BACKGROUND

Truncated tau appears to be specifically related to disease pathology and recent studies have shown the presence and elevation of several truncated tau species in Cerebrospinal fluid (CSF) of subjects with Alzheimer's disease (AD); however, the relevance of truncated Tau measurements in blood is still being studied.

OBJECTIVE

The aim of the current study was to assess the longitudinal associations between baseline levels of two novel blood biomarker candidates measuring truncated tau, Tau-A and Tau-C, and the risk of incident dementia and AD in elderly women.

METHODS

Using solid phase competitive ELISA, two tau fragments were detected in serum of 5,309 women from the Prospective Epidemiological Risk Factor study. The study was an observational, prospective study of Danish postmenopausal women. Subjects were followed with registry-linkage for up to 15 years (median follow-up time 13.7 years). Cox regression was used to assess the utility of the biomarker candidates in relation to dementia and AD.

RESULTS

High levels of Tau-A and Tau-C (above the median) in blood were associated with lower risk of dementia and AD (Tau-A: Dementia HR[95% CI] = 0.85[0.70-1.04]; AD 0.71[0.52-0.98] and Tau-C: Dementia 0.84[0.70-1.00]; AD 0.78[0.60-1.03]). Tau-C gave a very modest increase in the AUC in a 5-year prediction horizon as compared to a reference model with age and education, while a combination of the two did not improve their predictive capacity.

CONCLUSIONS

Measurement of tau in serum is feasible. The serological tau turnover profile may be related to the diagnosis and development of dementia and AD. The exact processing and profile in serum in relation to cognitive disorders remains to be further assessed to provide simple non-invasive tests to identify subjects with progressive cognitive disorders.

Atrial fibrillation, cognition and dementia: A review

Atrial fibrillation (AF) is one of the most common types of cardiac arrhythmia, particularly among older adults. AF confers a 5-fold risk for thromboembolic stroke as well as a 2-fold higher risk for congestive heart failure, morbidity, and mortality. Although stroke remains an important and impactful complication of AF, recent studies have shown that AF is independently associated with other neurological disorders, including cognitive impairment and dementia, even after adjusting for prior ischemic stroke. We performed a review of the published literature on the association between AF and cognitive status. Further, we reviewed studies investigating the underlying mechanisms for this association and/or reporting the impact of AF treatment on cognitive function. While most published studies demonstrate associations between AF and impaired cognition, no AF treatment has yet been associated with a reduced incidence of cognitive decline or dementia.

Age-related deficit accumulation and the risk of late-life dementia

Introduction

Many age-related health problems have been associated with dementia, leading to the hypothesis that late-life dementia may be determined less by specific risk factors, and more by the operation of multiple health deficits in the aggregate. Our study addressed (a) how the predictive value of dementia risk varies by the number of deficits considered and (b) how traditional (for example. vascular risks) and nontraditional risk factors (for example, foot problems, nasal congestion) compare in their predictive effects.

Methods

Older adults in the Canadian Study of Health and Aging who were cognitively healthy at baseline were analyzed (men, 2,902; women, 4,337). Over a 10-year period, 44.8% of men and 33.4% of women died; 7.4% of men and 9.1% of women without baseline cognitive impairment developed dementia. Self-rated health problems, including, but not restricted to, dementia risk factors, were coded as deficit present/absent. Different numbers of randomly selected variables were used to calculate various iterations of the index (that is, the proportion of deficits present in an individual. Risks for 10-year mortality and dementia outcomes were evaluated separately for men and women by using logistic regression, adjusted for age. The prediction accuracy was evaluated by using C-statistics.

Results

Age-adjusted odds ratios per additional deficit were 1.22 (95% confidence interval (CI), 1.18 to 1.26) in men and 1.14 (1.11 to 1.16) in women in relation to death, and 1.18 (1.12 to 1.25) in men and 1.08 (1.04 to 1.11) in women in relation to dementia. The predictive value increased with the number (n) of deficits considered, regardless of whether they were known dementia risks, and stabilized at n > 25. The all-factor index best predicted dementia (C-statistics, 0.67 ± 0.03).

Conclusions

The variety of items associated with dementias suggests that some part of the risk might relate more to aberrant repair processes, than to specifically toxic results. The epidemiology of late-life illness might best consider overall health status.