Putative Dementia Cases Fluctuate as a Function of Mini-Mental State Examination Cut-Off Points

Combining the AD8 and MMSE for community-based dementia screening

BACKGROUND

This study aimed to determine whether a cognitive test the Mini-Mental State Examination (MMSE) and the Ascertain Dementia 8 (AD8) instrument applied in combination could improve the accuracy of dementia detection in a community setting.

METHODS

Study participants were recruited from a community-based integrated screening program in Tainan, Taiwan. Participants completed the AD8 and were administered the Chinese version of the MMSE by psychologists. In addition, the presence of dementia was determined by neurologists based on the 2011 National Institute on Aging-Alzheimer's Association guidelines. Logistic regression analysis determined whether the combination of these two tests provided any additional information for dementia detection than either test alone. Receiver operating characteristic (ROC) curve analyses were conducted to explore the performances of different screening modalities in detecting dementia.

RESULT

In total, 282 participants with an average age of 69.31 ± 10.27 years were enrolled. The prevalence of dementia among participants aged ≥65 years was 9.29 %. The sensitivity and specificity of the AD8 applied alone for detecting dementia were 64.71 % and 87.89 %, respectively, and of the MMSE applied alone, after adjusting for education level, were 41.18 % and 84.50 %, respectively. Using a cutoff score of 21 for the MMSE resulted in sensitivity of 77.78 % and specificity of 73.58 %. The AD8 and MMSE when combined in parallel yielded 88.89 % sensitivity and 70.16 % specificity. The serial use of the AD8 followed by the MMSE yielded 50 % sensitivity and 93.02 % specificity. Except for when an MMSE cutoff value of 26 was applied, the sensitivity of all examined modalities was poor and specificity was moderate for detecting mild cognitive impairment. ROC curve analysis revealed that the parallel application of the MMSE and AD8 (area under the ROC curve [AUC]: 82.3 % [75.1 %-89.4 %]) resulted in better dementia detection accuracy than the AD8 alone (AUC: 73.3 % [60.7 %-85.9 %]), the MMSE alone (AUC: 77.4 % [67.6 %-87.3 %]), or serial test administration (AUC: 67.6 % [53.4 %-81.8 %]).

CONCLUSION

This study successfully demonstrated that the MMSE and AD8 combination for dementia screening could improve detection accuracy in a community setting.

FTIR Spectroscopy and Blood-Derived Extracellular Vesicles Duo in Alzheimer's Disease

Background

Alzheimer's disease (AD) diagnosis is difficult, and new accurate tools based on peripheral biofluids are urgently needed. Extracellular vesicles (EVs) emerged as a valuable source of biomarker profiles for AD, since their cargo is disease-specific and these can be easily isolated from easily accessible biofluids, as blood. Fourier Transform Infrared (FTIR) spectroscopy can be employed to analyze EVs and obtain the spectroscopic profiles from different regions of the spectra, simultaneously characterizing carbohydrates, nucleic acids, proteins, and lipids.

Objective

The aim of this study was to identify blood-derived EVs (bdEVs) spectroscopic signatures with AD discriminatory potential.

Methods

Herein, FTIR spectra of bdEVs from two biofluids (serum and plasma) and distinct sets of Controls and AD cases were acquired, and EVs' spectra analyzed.

Results

Analysis of bdEVs second derivative peaks area revealed differences between Controls and AD cases in distinct spectra regions, assigned to carbohydrates and nucleic acids, amides, and lipids.

Conclusions

EVs' spectroscopic profiles presented AD discriminatory value, supporting the use of bdEVs combined with FTIR as a screening or complementary tool for AD diagnosis.

Monitoring clusterin and fibrillar structures in aging and dementia

Objective

Clusterin is involved in a variety of physiological processes, including proteostasis. Several clusterin polymorphisms were associated with an increased risk of developing Alzheimer's disease, the world-leading cause of dementia. Herein, the effect of a clusterin polymorphism, aging and dementia in the levels of clusterin in human plasma were analysed in a primary care-based cohort, and the association of this chaperone with fibrillar structures discussed.

Methods

64 individuals with dementia (CDR≥1) and 64 age- and sex-matched Controls from a Portuguese cohort were genotyped for CLU rs1136000 polymorphism, and the plasma levels of clusterin and fibrils were assessed.

Results

An increased prevalence of the CC genotype was observed for the dementia group, although no significant robustness was achieved. CLU rs11136000 SNP did not significantly change plasma clusterin levels in demented individuals. Instead, clusterin levels decreased with aging and even more in individuals with dementia. Importantly, plasma clusterin levels correlated with the presence of fibrillar structures in Control individuals, but not in those with dementia.

Conclusion

This study reveals a significant decrease in plasma clusterin in demented individuals with aging, which related to altered clusterin-fibrils dynamics. Potentially, plasma clusterin and its association with fibrillar structures can be used to monitor dementia progression along aging.

BIN1 rs744373 SNP and APOE alleles specifically associate to common diseases

APOE ε4 and BIN1 are the two main genetic risk factors for sporadic Alzheimer's Disease (AD). Among several BIN1 variants, the rs744373 is frequently associated with AD risk by contributing to tau pathology and poor cognitive performance. This study addressed the association of APOE and BIN1 rs744373 to specific characteristics in a Portuguese primary care-based study group, denoted pcb-Cohort. The study included 590 participants from five primary care health centers in the Aveiro district of Portugal. Individuals were evaluated and scored for cognitive and clinical characteristics, and blood samples were collected from the volunteers meeting the inclusion and exclusion criteria (N = 505). APOE and BIN1 genotypes were determined, and their association with cognitive characteristics and other diseases that might contribute to cognitive deficits, namely depression, hypertension, type 2 diabetes, dyslipidemia, osteoarticular diseases, gastrointestinal diseases, cardiovascular and respiratory diseases, was assessed. The diseases attributed to the study group were those previously diagnosed and confirmed by specialists. The results generated through multivariate analysis show that APOE ε4 carriers significantly associated with poorer cognitive performance (OR = 2.527; p = 0.031). Additionally, there was a significant risk of dyslipidemia for APOE ε4 carriers (OR = 1.804; p = 0.036), whereas BIN1 rs744373 risk-allele carriers were at a significantly lower risk of having dyslipidemia (OR = 0.558; p = 0.006). Correlations were evident for respiratory diseases in which APOE ε4 showed a protective tendency (OR = 0.515; p = 0.088), and BIN1 had a significative protective profile (OR = 0.556; p = 0.026). Not of statistical significance, APOE ε2 showed a trend to protect against type 2 diabetes (OR = 0.342; p = 0.093), in contrast BIN1 rs744373 risk-allele carriers were more likely to exhibit the disease (OR = 1.491; p = 0.099). The data here presented clearly show, for the first time, that the two top genetic risk factors for sporadic AD impact a similar group of common diseases, namely dyslipidemia, respiratory diseases, and type 2 diabetes.

A Bioinformatics Approach Toward Unravelling the Synaptic Molecular Crosstalk Between Alzheimer’s Disease and Diabetes

Background: Increasing evidence links impaired brain insulin signaling and insulin resistance to the development of Alzheimer’s disease (AD). Objective: This evidence prompted a search for molecular players common to AD and diabetes mellitus (DM). Methods: The work incorporated studies based on a primary care-based cohort (pcb-Cohort) and a bioinformatics analysis to identify central nodes, that are key players in AD and insulin signaling (IS) pathways. The interactome for each of these key proteins was retrieved and network maps were developed for AD and IS. Synaptic enrichment was performed to reveal synaptic common hubs. Results: Cohort analysis showed that individuals with DM exhibited a correlation with poor performance in the Mini-Mental State Examination (MMSE) cognitive test. Additionally, APOE ɛ2 allele carriers appear to potentially be relatively more protected against both DM and cognitive deficits. Ten clusters were identified in this network and 32 key synaptic proteins were common to AD and IS. Given the relevance of signaling pathways, another network was constructed focusing on protein kinases and protein phosphatases, and the top 6 kinase nodes (LRRK2, GSK3B, AKT1, EGFR, MAPK1, and FYN) were further analyzed. Conclusion: This allowed the elaboration of signaling cascades directly impacting AβPP and tau, whereby distinct signaling pathway play a major role and strengthen an AD-IS link at a molecular level.

Novel Exosome Biomarker Candidates for Alzheimer's Disease Unravelled Through Mass Spectrometry Analysis

Exosomes are small extracellular vesicles (EVs) present in human biofluids that can transport specific disease-associated molecules. Consequently blood-derived exosomes have emerged as important peripheral biomarker sources for a wide range of diseases, among them Alzheimer’s disease (AD). Although there is no effective cure for AD, an accurate diagnosis, relying on easily accessible peripheral biofluids, is still necessary to discriminate this disease from other dementias, test potential therapies and even monitor rate of disease progression. The ultimate goal is to produce a cost-effective and widely available alternative, which can also be employed as a first clinical screen. In this study, EVs with exosome-like characteristics were isolated from serum of Controls and AD cases through precipitation- and column-based methods, followed by mass spectrometry analysis. The resulting proteomes were characterized by Gene Ontology (GO) and multivariate analyses. Although GO terms were similar for exosomes’ proteomes of Controls and ADs, using both methodologies, a clear segregation of disease cases was obtained when using the precipitation-based method. Nine significantly different abundant proteins were identified between Controls and AD cases, representing putative biomarker candidate targets. Among them are AACT and C4BPα, two Aβ-binding proteins, whose exosome levels were further validated in individuals from independent cohorts using antibody-based approaches. The findings discussed represent an important contribution to the identification of novel exosomal biomarker candidates useful as potential blood-based tools for AD diagnosis.

Potential of FTIR Spectroscopy Applied to Exosomes for Alzheimer's Disease Discrimination: A Pilot Study

Alzheimer's disease (AD) diagnosis is based on psychological and imaging tests but can also include monitoring cerebrospinal fluid (CSF) biomarkers. However, CSF based-neurochemical approaches are expensive and invasive, limiting their use to well-equipped settings. In contrast, blood-based biomarkers are minimally invasive, cost-effective, and a widely accessible alternative. Blood-derived exosomes have recently emerged as a reliable AD biomarker source, carrying disease-specific cargo. Fourier-transformed infrared (FTIR) spectroscopy meets the criteria for an ideal diagnostic methodology since it is rapid, easy to implement, and has high reproducibility. This metabolome-based technique is useful for diagnosing a broad range of diseases, although to our knowledge, no reports for FTIR spectroscopy applied to exosomes in AD exist. In this ground-breaking pilot study, FTIR spectra of serum and serum-derived exosomes from two independent cohorts were acquired and analyzed using multivariate analysis. The regional UA-cohort includes 9 individuals, clinically diagnosed with AD, mean age of 78.7 years old; and the UMG-cohort comprises 12 individuals, clinically diagnosed with AD (based on molecular and/or imaging data), mean age of 73.2 years old. Unsupervised principal component analysis of FTIR spectra of serum-derived exosomes revealed higher discriminatory value for AD cases when compared to serum as a whole. Consistently, the partial least-squares analysis revealed that serum-derived exosomes present higher correlations than serum. In addition, the second derivative peak area calculation also revealed significant differences among Controls and AD cases. The results obtained suggest that this methodology can discriminate cases from Controls and thus be potential useful to assist in AD clinical diagnosis.

Exosomal Aβ-Binding Proteins Identified by "In Silico" Analysis Represent Putative Blood-Derived Biomarker Candidates for Alzheimer´s Disease

The potential of exosomes as biomarker resources for diagnostics and even for therapeutics has intensified research in the field, including in the context of Alzheimer´s disease (AD). The search for disease biomarkers in peripheral biofluids is advancing mainly due to the easy access it offers. In the study presented here, emphasis was given to the bioinformatic identification of putative exosomal candidates for AD. The exosomal proteomes of cerebrospinal fluid (CSF), serum and plasma, were obtained from three databases (ExoCarta, EVpedia and Vesiclepedia), and complemented with additional exosomal proteins already associated with AD but not found in the databases. The final biofluids’ proteomes were submitted to gene ontology (GO) enrichment analysis and the exosomal Aβ-binding proteins that can constitute putative candidates were identified. Among these candidates, gelsolin, a protein known to be involved in inhibiting Abeta fibril formation, was identified, and it was tested in human samples. The levels of this Aβ-binding protein, with anti-amyloidogenic properties, were assessed in serum-derived exosomes isolated from controls and individuals with dementia, including AD cases, and revealed altered expression patterns. Identification of potential peripheral biomarker candidates for AD may be useful, not only for early disease diagnosis but also in drug trials and to monitor disease progression, allowing for a timely therapeutic intervention, which will positively impact the patient’s quality of life.

The association of metabolic syndrome and cognitive impairment in Jidong of China: a cross-sectional study

BACKGROUND

Metabolic syndrome (Mets) is prevalent in the general population and has been reported to be an independent risk factor for cognitive impairment. This study aimed to investigate the association of Mets with the risk of cognitive impairment.

METHODS

We studied 5854 participants from the Jidong community. Cognitive function was assessed by the Mini-Mental State of Examination (MMSE) scale. Mets was diagnosed according to the International Diabetes Federation criteria. We used logistic regression analysis to investigate the association of metabolic syndrome with the risk of cognitive impairment.

RESULT

Among the 5854 adults included in the study, the age mean (SD) of age was 44 (13.57) years, and 2916 (50.34%) were male. There was a higher (56.03%) cognitive impairment incidence rate among participants with Mets than among those without Mets. In addition, there was a significant association between Mets and cognitive impairment (OR: 2.39, 95% CI: 2.00-2.86, P < 0.05) after adjusting for potential confounders, including age, gender, education level, marital status, smoking and alcohol consumption status. Regarding the 5 Mets components, abdominal obesity and elevated blood pressure were associated with the risk of Mets (OR: 1.36, 95% CI: 1.09-1.70, P < 0.001; OR: 1.32, 95% CI: 1.07-1.63, P < 0.05). Moreover, the strongest statistical correlation (adjusted OR: 1.86, 95% CI: 1.22-2.83, P < 0.05) was found when the number of Mets components was three.

CONCLUSION

Our study suggested that Mets was associated with cognitive impairment and that abdominal obesity and hypertension were associated with an increased risk of cognitive impairment.

The efficacy of transcranial alternating current stimulation for treating post-stroke depression: Study Protocol Clinical Trial (SPIRIT Compliant)

BACKGROUND

The treatment of post-stroke depression (PSD) with anti-depressant drugs is partly practical. Transcranial alternating current stimulation (tACS) offers the potential for a novel treatment modality for adult patients with PSD. In this study, we will assess the efficacy and safety of tACS for treating PSD and explore its effect on gamma and beta-oscillations involving in emotional regulation.

METHODS

The prospective study is an 8-week, double-blind, randomized, placebo-controlled trial. Seventy eligible participants with mild to moderate PSD aged between 18 years and 70 years will be recruited and randomly assigned to either active tACS intervention group or sham group. Daily 40-minute, 77.5-Hz, 15-mA sessions of active or sham tACS targeting the forehead and both mastoid areas on weekdays for 4 consecutive weeks (week 4), and an additional 4-week observational period (week 8) will be followed up. The primary outcome is the proportion of participants having an improvement at week 8 according to the Hamilton Depression Rating Scale 17-Item (HAMD-17) score, including the proportion of participants having a decrease of ≥ 50% in HAMD-17 score or clinical recovery (HAMD-17 score ≤ 7). Secondary outcomes include neurological function, independence level, activities of daily living, disease severity, anxiety, and cognitive function. The exploratory outcomes are gamma and beta-oscillations assessed at baseline, week 4, and week 8. Data will be analyzed by logistical regression analyses and mixed-effects models.

DISCUSSION

The study will be the first randomized controlled trial to evaluate the efficacy and safety of tACS at a 77.5-Hz frequency and 15-mA current in reducing depressive severity in patients with PSD. The results of the study will present a base for future studies on the tACS in PSD and its possible mechanism.

TRIAL REGISTRATION NUMBER

NCT03903068, pre-results.

EEG spectral power abnormalities and their relationship with cognitive dysfunction in patients with Alzheimer's disease and type 2 diabetes

Rhythmic neural activity has been proposed to play a fundamental role in cognition. Both healthy and pathological aging are characterized by frequency-specific changes in oscillatory activity. However, the cognitive relevance of these changes across the spectrum from normal to pathological aging remains unknown. We examined electroencephalography (EEG) correlates of cognitive function in healthy aging and 2 of the most prominent and debilitating age-related disorders: type 2 diabetes mellitus (T2DM) and Alzheimer's disease (AD). Relative to healthy controls (HC), patients with AD were impaired on nearly every cognitive measure, whereas patients with T2DM performed worse mainly on learning and memory tests. A continuum of alterations in resting-state EEG was associated with pathological aging, generally characterized by reduced alpha (α) and beta (β) power (AD < T2DM < HC) and increased delta (δ) and theta (θ) power (AD > T2DM > HC), with some variations across different brain regions. There were also reductions in the frequency and power density of the posterior dominant rhythm in AD. The ratio of (α + β)/(δ + θ) was specifically associated with cognitive function in a domain- and diagnosis-specific manner. The results thus captured both similarities and differences in the pathophysiology of cerebral oscillations in T2DM and AD. Overall, pathological brain aging is marked by a shift in oscillatory power from higher to lower frequencies, which can be captured by a single cognitively relevant measure of the ratio of (α + β) over (δ + θ) power.

Monitoring plasma protein aggregation during aging using conformation-specific antibodies and FTIR spectroscopy

The loss of proteostasis during aging has been well described using different models, however little is known with respect to protein aggregation levels in biofluids with aging. Therefore, the aim of this study was to assess the pattern of age-related protein aggregation in human plasma using two distinct approaches: analysis with conformation-specific antibodies and FTIR spectroscopy. The latter has been widely used in biomedical research to study protein conformational changes in health and disease. Samples from a primary care based-cohort from the Aveiro region, Portugal, were used for slot-blot analyses followed by immunodetection with conformation-specific antibodies and for the acquisition of FTIR spectra. Immunoblot analyses revealed an age-dependent evolution of the protein conformational profile in human plasma, towards a decrease in prefibrillar oligomers and an increase in fibrillar structures. This finding was also supported by PLS-R multivariate analysis of FTIR data, where a positive correlation between the age of the donors and secondary structure of plasma proteins could be observed. Samples from younger donors are characterized by antiparallel β-sheet-containing structures while intermolecular β-sheets characterized older samples. Exclusion of age-associated co-morbidities improved the correlation between protein conformational profiles and aging. The results reveal structural changes in human plasma proteins from middle to old age, confirming the age-associated changes in protein aggregation, and support the applicability of FTIR as a reliable approach to study proteostasis during aging.

B. da Cruz e Silva O, Henriques AG. Exosome isolation from distinct biofluids using precipitation and column-based approaches

The potential of exosomes as biomarker resources for diagnostics, prognostics and even for therapeutics is an area of intense research. Despite the various approaches available, there is no consensus with respect to the best methodology for isolating exosomes and to provide substantial yields with reliable quality. Differential centrifugation is the most commonly used method but it is time-consuming and requires large sample volumes, thus alternative methods are urgently needed. In this study two precipitation-based methods and one column-based approach were compared for exosome isolation from distinct biofluids (serum, plasma and cerebrospinal fluid). Exosome characterization included morphological analyses, determination of particle concentration, stability and exosome preparations’ purity, using different complementary approaches such as Nanoparticle Tracking Analysis, Electrophoretic Light Scattering, Transmission Electron Microscopy, EXOCET colorimetric assay, protein quantification methods and western blotting. The three commercial kits tested successfully isolated exosomes from the biofluids under study, although ExoS showed the best performance in terms of exosome yield and purity. Data shows that methods other than differential centrifugation can be applied to quickly and efficiently isolate exosomes from reduced biofluid volumes. The possibility to use small volumes is fundamental in the context of translational and clinical research, thus the results here presented contribute significantly in this respect.